Development of Sustainable Urban Transport System Investigation (SUSI) A Decision Support System for the Usage of Alternative Fuels in Public Transportation

Panagiotis Georgousis Sönke Behrends

Examiner: Magnus Blinge

Division of Logistics and Transportation Department of Technology Management and Economics CHALMERS UNIVERSITY OF TECHNOLOGY Göteborg, Sweden 2005

Master’s thesis E 2005:053

Acknowledgements

Acknowledgements The thesis project started in June 2004 and came to an end in January 2005. Throughout this period we became acquainted with the inspiring and dynamic arena of alternative fuel research, especially with the field of hydrogen and fuel cells. We would like to express our gratitude and appreciation towards the financers of our thesis ECTOS, Vinnova and TFK and everyone who provided assistance, advice and guidance throughout our thesis work and the development of SUSI. First of all, we are sincerely grateful to our supervisor Dr. Magnus Blinge and our advisor MSc Elisabeth Sörheim for guiding and supporting us with our work. We are also grateful to our colleagues at TFK for the inspiring and pleasant working atmosphere and assistance throughout the project. We also would like to thank Dipl.-Ing. Michael Faltenbacher for his help; his advice on emissions inventory calculations and general assistance were priceless. We are also grateful to Mrs. Maria Hildur Maack for her assistance in getting started with the project and her beneficial guidance during our visit in Iceland. Furthermore, we would like to thank all people working for the ECTOS, CUTE, STEP projects and participants of the “First Experiences of European Fuel Cell Bus Demonstration Projects” conference in London, June 04 and “2nd International Fuel Cell Bus Workshop” conference in Porto, November 04; particularly everyone that we interviewed and who shared his/her time and experiences with us. Additionally, we would like to express our gratitude towards Chalmers University of Technology, Graduate Business School of Handelshögskolan and Malmsten foundation for providing paramount study conditions and an international and inspiring atmosphere for our MSc studies. Finally, we would like to thank our families and friends for their encouragement, support and patience with the process of our thesis work.

Göteborg, 31st January 2005

………………………………. Sönke Behrends

………………………………. Panagiotis Georgousis I

Abstract

Abstract Worldwide energy demand is growing at an alarming rate. This increased demand is being met largely by fossil resources, which entails climate change, growing risk of energy supply disruptions, price volatility and air pollution. Transportation is responsible for this to a great extend. Therefore, the European Union seeks to replace 20% of conventional fuels with alternative fuels by 2020, 5% should be hydrogen. Currently there are three large scale demonstration projects concerning the usage of hydrogen and fuel cells in public transportation: ECTOS, CUTE and STEP; different methods of utilizing hydrogen using different production methods and resources are presented. Well-to-Wheel pathways of alternative fuels differ in environmental, economical, technical and socio-economic performance; furthermore differing local conditions influence their performance significantly. Decision makers in public transportation do not always possess the required knowledge in order to evaluate correctly the differing impact of alternative fuels. This thesis develops the Sustainable Urban Transport System Investigation (SUSI); a computerized model developed with MS Access, which will be able to compare the usage schemes of all alternative fuels and propose adequate solutions for production and distribution taking local conditions into account. The complexity of the hydrogen production and distribution systems is presented and used as sample data for the development of the model. The outcome of the thesis is a well structured model for decision makers in public transportation providing: a) the structure for a pedagogic "handbook" about the usage of alternative fuels in public transportation and b) the structure for a decision support system for alternative fuel well-to-wheels pathways. The thesis report provides the theoretical background for the development of the model and a user manual in order to assist further development. Key words: alternative fuels, hydrogen, well-to-wheels, urban transportation, decision support system, MS Access.

II

Table of contents

Table of contents ACKNOWLEDGEMENTS

I

ABSTRACT

II

TABLE OF CONTENTS

III

LIST OF FIGURES

V

LIST OF TABLES

VII

LIST OF ABBREVIATIONS

VIII

1

INTRODUCTION

1

1.1 Background 1.1.1 The energy challenge 1.1.2 The role of the transportation sector 1.1.3 EU policy 1.1.4 The fuel cell bus demonstration projects ECTOS, CUTE, STEP

1 1 2 4 4

1.2

Aim

6

1.3

Problem Analysis

7

1.4

Limitations

8

1.5

Methods

8

1.6

Disposition

9

2

HYDROGEN AND FUEL CELLS

11

2.1 Why Hydrogen, why fuel cells? 2.1.1 Hydrogen 2.1.2 Fuel cells 2.1.3 Benefits of hydrogen powered fuel cells 2.1.4 Challenges for the hydrogen/fuel cell market introduction

11 11 12 13 14

2.2 Hydrogen production 2.2.1 Water-Electrolysis 2.2.2 Steam reforming 2.2.3 Partial oxidation of heavy hydrocarbons 2.2.4 Autothermal reforming 2.2.5 Gasification 2.2.6 CB&H Process (Kværner) 2.2.7 Thermochemical cycles 2.2.8 Photo-electrochemical production 2.2.9 Biological production 2.2.10 Hydrogen as a by-product 2.2.11 Summary

15 15 16 18 18 18 19 19 20 20 21 21

2.3 Hydrogen infrastructure 2.3.1 Hydrogen storage

22 22

III

Table of contents

2.3.2 2.3.3

3

Hydrogen distribution and conditioning Hydrogen filling stations

THEORY

25 27

28

3.1 Well-to-wheels pathway evaluation methods 3.1.1 Live Cycle Assessment (LCA) 3.1.2 Well-to-Wheels Analysis (WtW) 3.1.3 Summary of WtW pathway evaluation methods

28 28 31 33

3.2 Decision factors for alternative fuels 3.2.1 MUD evaluation 3.2.2 Environmental impact 3.2.3 Long term access 3.2.4 Public attitude 3.2.5 Reliability 3.2.6 Total economics

34 34 35 37 38 38 38

3.3 Decision support systems and databases 3.3.1 Decision support system 3.3.2 Databases

39 39 41

4

SUSTAINABLE URBAN TRANSPORT SYSTEM INVESTIGATION (SUSI)

44

4.1 Defintion of Goal and Scope 4.1.1 Descriptive Model 4.1.2 Decision Support System 4.1.3 Summary of Definition of Goal and Scope

44 44 45 46

4.2 System Description 4.2.1 Main concept 4.2.2 Data elements 4.2.3 Implementation

46 47 51 52

4.3 Decision Support System 4.3.1 Inventory Analysis 4.3.2 Impact Assessment 4.3.3 Delimitation process

54 54 59 61

4.4 Results 4.4.1 Sample Data 4.4.2 Application of SUSI

61 61 64

5

CONCLUSIONS AND RECOMMENDATIONS

REFERENCES APPENDIX 1: RELATIONSHIPS OF BASIC ACCESS TABLES APPENDIX 2: SUSI MANUAL

IV

67 69

List of Figures

List of Figures Figure 1: Structure of primary energy demand in EU-25

1

Figure 2: Share of imports in EU-25 energy consumption

2

Figure 3: Energy consumption in the EU-25 by sector (2030)

3

Figure 4: Energy use by mode in 2001

3

Figure 5: EU plan of diesel and gasoline substitution by alternative motor fuels in %

4

Figure 6: Hydrogen – supply and demand

11

Figure 7: Fuel Cells - Fuels and applications

12

Figure 8: PEM fuel cell

13

Figure 9: Status of hydrogen production technologies

15

Figure 10: Mode of Functioning of a Water Electrolyser

16

Figure 11: Mode of functioning of a steam reformer

17

Figure 12: Status of hydrogen storage technologies

23

Figure 13: Status of hydrogen distribution and conditioning technologies

25

Figure 14: Status of hydrogen filling station technologies

27

Figure 15: ISO 14040 LCA framework

29

Figure 16: LCA of a FC Bus System including system boundaries

30

Figure 17: Concept of WtT analysis of the European WtW study

32

Figure 18: GREET fuel cycle concept

33

Figure 19: Local, regional and global impact categories

35

Figure 20: DSS Concept

40

Figure 21: Entity-Relation model of a relational dbase

41

Figure 22: Example data of a relational dbase

41

Figure 23: Dbase developing procedure

43

Figure 24: LCA structure of a well-to-wheels pathway

47

Figure 25: SUSI Concept

49

Figure 26: Example of a Well-to-Wheel path in SUSI

51

Figure 27: DSS Stakeholders

52

Figure 28: Dbase developing procedure

53

Figure 29: Sprague DSS concept vs. SUSI concept

53

V

List of Figures

Figure 30: Concept of the Delimitation process

61

Figure 31: Electricity Feedstock Paths – Resources [50%]

62

Figure 32: SUSI Well-to-Wheels Results (EU Average Conditions)

64

Figure 33: SUSI Well-to-Wheels Results (Göteborg Conditions)

65

Figure 34: SUSI Well-to-Wheels Results (Hamburg Conditions)

65

VI

List of Tables

List of Tables Table 1: List of interviews

9

Table 2: Hydrogen production methods, feedstock and resources

22

Table 3: Road transportation emissions and environmental impact categories

37

Table 4: Example feedstock path calculations

56

Table 5: Example Fuel path calculations - direct emissions

57

Table 6: Example Fuel Path Calculations - Indirect emissions from Feedstock path

58

Table 7: Example Fuel Path Calculations - Total Well-to-Tank

58

Table 8: Example Tank-to-Wheels

59

Table 9: Example total Well-to-Wheels emissions

59

Table 10: Electricity Feedstock Paths - Resources

62

VII

List of Abbreviations

List of Abbreviations CH4

Methane

Cl2

Chlorine

CO

Carbon Monoxide

CO2

Carbon Dioxide

CUTE

Clean Urban Transport for Europe

Dbase

Database

ECTOS

Ecological City Transport

FC

Fuel Cell

GHG

Greenhouse Gases

H2

Hydrogen

ICE

Internal Combustion Engine

LCA

Life Cycle Assessment

LCI

Life Cycle Inventory

MJ

Megajoule

N2O

Dinitrogen Oxide

NG

Natural Gas

NMVOC

Non Methane Volatile Organic Compounds

NOx

Nitrous oxides

PM

Particulate Matter

SO2

Sulphur Dioxide

STEP

Sustainable Transport Energy Perth

SUSI

Sustainable Urban Transport System Investigation

TtW

Tank-to-Wheels

WtT

Well-to-Tank

WtW

Well-to-Wheels

VIII

Introduction

1

Introduction

The thesis report focuses on facilitating decision making in the field of alternative fuels in public transportation. In this introductory chapter the background, the aim, problem analysis, limitations, methodology and the disposition of the thesis are presented.

1.1

Background

1.1.1

The energy challenge

Energy is the lifeblood of today’s society and economy. Our economic, social and physical welfare depends on the sufficient and uninterrupted supply of energy which we take for granted. As a result energy demand in the European Union continues to grow at a high rate; the EU predicts the primary energy demand to increase by 19% between 2000 and 2030 (European Commission - Directorate-General for Energy and Transport, 2003b). To meet this increased demand mainly fossil fuels will be used with the result that 82% of the total primary energy demand in 2030 will be met by the fossil sources coal, oil and natural gas (Figure 1) that emit both greenhouse gases and other pollutants. 100% 90%

4,6%

5,9%

7,4%

8,0%

8,6%

28,6%

31,6%

32,0%

35,8%

34,8%

16,6% 22,8%

80% 70% 60%

38,5% 38,4%

50%

36,7%

40% 30%

27,7%

18,4%

13,6%

20% 10%

13,3%

15,0%

12,7%

14,4%

13,7%

11,3%

9,5%

1990

2000

2010

2020

2030

0%

Nuclear

Coal

Oil

Natural Gas

Renewables

Figure 1: Structure of primary energy demand in EU-251

Because of the increased use of fossil fuels there are three challenges the EU has to cope with: The climate change challenge The increasing energy demand will mostly be met by fossil fuels causing the emissions of greenhouse gases to exceed their 1990 level by 20% by 2030 (European Commission Directorate-General for Energy and Transport, 2003b). Consequently the EU will fail in 1

European Commission - Directorate-General for Energy and Transport: European energy and transport trends to 2030, Office for Official Publications of the European Communities. Luxemburg, 2003b

1

Introduction

fulfilling its Kyoto commitments cutting its greenhouse gas emissions to 8% below the 1990 levels by 2008-2012 (European Commission - Directorate-General for Research, 2003). Furthermore other emissions with local and regional effects will affect the air quality, increasing the possibility of public health problems. The challenge of economic ‘disruptions’ Because the reserves of fossil fuels are diminishing, in 50 years there will be almost no oil and gas left, that can be extracted in an economically defendable way (European Commission - Directorate-General for Energy and Transport, 2002b). Thus the increasing demand for primary energy faces a limited offer. An erratic price increase for primary energy in the long term is likely to occur. The rise in fuel prices creates monetary and trade imbalances which are harmful to the EU’s economic health. The challenge of dependence on external energy sources The European Union will become increasingly dependent on external energy sources (European Commission - Directorate-General for Energy and Transport, 2001a). The sources of fossil fuels are confined to a few areas mainly outside of the European Union. Based on current forecasts the share of net imports of the primary energy is projected to grow from about 50 % today to 66% until 2030 (Figure 2). The unstable political conditions in most of the fossil fuel exporting countries put continuous supply at risk endangering the energy supply security of the EU. 70% 60% 50% 40% Net imports 30% 20% 10% 0% 1990

2000

2010

2020

2030

Figure 2: Share of imports in EU-25 energy consumption2

1.1.2

The role of the transportation sector

The main driver for the increasing energy demand and the dependence on fossil fuels is the transportation sector. With a three-time bigger than average growth of the total energy consumption between 1990 and 2000, the transportation sector was by far the fastest growing 2

European Commission - Directorate-General for Energy and Transport: European energy and transport trends to 2030, Office for Official Publications of the European Communities. Luxemburg, 2003b.

2

Introduction

energy consuming sector in the EU-25 in the last decade (European Commission Directorate-General for Energy and Transport, 2003b). Although on a smaller level the major role of the transportation sector in final energy demand growth is projected to continue (plus 35% from 2000 to 2030) with the result that almost one third of the total energy will be consumed by the transportation sector (Figure 3). transport 32%

domestic and tertiary 40%

industry 28%

Figure 3: Energy consumption in the EU-25 by sector (2030) 3

The energy supply of the transportation sector almost entirely depends on oil; 98% of total transport energy is based on oil (European Commission - Directorate-General for Energy and Transport, 2001b). Thus the sector represents 67% of the final oil demand. As a result 90% of the expected increase in CO2 emissions will be emitted by the transportation sector. Road transport is particular responsible since it consumes 82% of the energy use of the sector (Figure 4) generating 85% of the sector’s CO2 emissions (European Commission Directorate-General for Energy and Transport, 2004). Air 14% Rail 2%

Inland navigati on 2%

Road 82%

Figure 4: Energy use by mode in 20014

Consequently, the road transportation sector is the area, where actions absolutely have to be taken to cope with the challenges of climate change, economic disruption and security of energy supply.

3

European Commission - Directorate-General for Energy and Transport: European energy and transport trends to 2030, Office for Official Publications of the European Communities. Luxemburg, 2003b. 4 European Commission - Directorate-General for Energy and Transport: European Energy and Transport in Figures, Office for Official Publications of the European Communities. Luxemburg, 2003a.

3

Introduction

1.1.3

EU policy

The EU policy includes three kinds of actions to reduce oil use in road transportation: The first action is to save transport energy through management of the demand for transportation. Reducing the demand for transportation would save transport energy as well as transferring traffic from the comparably high-energy-consuming road transport to more energy-efficient transport modes like rail. The second measurement is to enhance the energyefficiency of road vehicles. Finally oil use in road transport can be reduced by substituting oilbased fuels with alternative fuels. Therefore a coherent energy strategy is required addressing both energy supply and demand. Concerning fuel substitution it is the objective of the EU to replace 20% of conventional fuels with substitute fuels by 2020 (Figure 5). The most promising forms are bio fuel in the short and medium term, natural gas in the medium and long term. In the very long term the EU seeks to build an economy based on hydrogen and on hydrogen powered fuel cells. 10% 9%

Bio fuel

8%

Natural gas

7%

Hydrogen

10%

8% 7%

6%

6%

5%

5%

5%

4% 3% 2% 1%

2%

2%

2%

0%

0%0%

0%

2005

2010

2015

2020

Figure 5: EU plan of diesel and gasoline substitution by alternative motor fuels in %5

1.1.4

The fuel cell bus demonstration projects ECTOS, CUTE, STEP

The hydrogen/fuel cell technology is still at the very beginning of its development and is not yet ready for introduction to the transport market. To achieve the ambitious goal of substituting 5% of conventional fuels with hydrogen by 2020 governmental support has to be given. Among others, one action is to carry out prototype demonstration and pilot programmes to extend the existing technology evaluation exercises into the market. The aim of these “lighthouse” projects is to demonstrate the feasibility of the technology and to build the required infrastructure in order to support its market introduction (Karlström, 2002). 5

Sabater, I. Conference First Experiences of European Fuel Cell Bus Demonstration Projects, London, 2004/06/15.

4

Introduction

Thus the EU set up the CUTE (Clean Urban Transport for Europe) project with the target to develop a role for hydrogen and fuel cells in public transportation. The project started in November 2001 and will last until May 2006 (European Commission - Directorate-General for Energy and Transport, 2002a). CUTE is a field trial of fuel cell buses and the hydrogen infrastructure. Three buses operate in each of the nine participating cities under real-life conditions. The participating cities are: ƒ

Amsterdam,

ƒ

Barcelona,

ƒ

Hamburg,

ƒ

London,

ƒ

Luxemburg,

ƒ

Madrid,

ƒ

Porto,

ƒ

Stockholm and

ƒ

Stuttgart

Furthermore there are 3 more buses within the associated project ECTOS (Ecological City Transport System) in Reykjavik, Iceland and 3 buses within STEP (Sustainable Transport Energy) in Perth, Australia. The objectives of the projects are: ƒ

Demonstration of a fuel cell bus fleet under a variety of operating conditions,

ƒ

Design, construction and operation of the required hydrogen infrastructure

ƒ

Life cycle analysis of the entire FC bus system and comparison to conventional bus systems, including economic analysis of the H2 infrastructure

ƒ

Handling quality & safety issues of the different H2 infrastructure solutions

ƒ

Education and training of involved personnel

ƒ

Dissemination of results

The overall goal of the fuel cell bus demonstration projects CUTE, ECTOS and STEP is to learn about the hydrogen/fuel cell transport system. To put the results in use for decision makers a tool is necessary that includes the lesson learnt in the projects as well as taking other sources into consideration.

5

Introduction

1.2

Aim

Today, decision makers in public transportation do not always possess the required knowledge about alternative fuels in order to evaluate correctly the impact of different kind of well-to-wheels pathways under the special conditions of their location. There is indeed a multitude of research, studies and information tools about alternative fuels that could help to make the ‘right’ decision, but since using these supportive sources is complex and require specific knowledge as well as a lot of time, still decisions are made on intuitive basis using subjective criteria (Ottosson, 2004). The purpose of this thesis is to develop the structure of a decision support system (DSS) by compiling existing knowledge about alternative fuels and the findings from the CUTE, ECTOS and STEP project into a holistic descriptive model called “Sustainable Urban Transport System Investigation (SUSI)”. The Model also shall be open to include relevant findings and experiences from other research projects on alternative fuels but the main information source is CUTE, ECTOS and STEP. The expected outcome is a well structured descriptive model of limited complexity developed for comparisons of the functionalities, advantages and disadvantages of different well-to-wheels pathways with the focus on hydrogen and fuel cell technology. Relevant factors identified in the CUTE, ECTOS and STEP project and from other areas of research will be included. With this model the user or decision maker can get a holistic overview about alternative well-to-wheels pathways. The developed SUSI shall present research results and the outcome of studies about alternative fuels in a structured way on a general level for the decision maker. By reducing the complexity in this way, SUSI can be used as a pedagogic ‘handbook’ for guiding other cities and regions that are considering an implementation of an alternative fuel bus system. By this the decisions can be based more on knowledge than on intuition. Of course, subjective criteria can not be avoided as long as human bias is involved, but the model can help to reduce its influence.

6

Introduction

1.3

Problem Analysis

The purpose of SUSI is to support decision makers in finding the “best” well-to-wheels pathway for their cities by comparing the functionalities, advantages and disadvantages of different well-to-wheels pathways. In order to achieve this, three main issues have to be taken into consideration during the development of SUSI: First, to find the best well-to-wheels pathway for a certain decision maker of a certain city, the total life cycle of the fuel has to be considered. For example a vehicle using a certain fuel might produce almost no emissions and therefore this fuel seems to be a promising way to reduce emissions. On the other hand there might be lots of emissions created during the production phase of the fuel with the result that this well-to-wheels pathway is not a good solution at all. Thus, an examination is necessary of the entire chain from producing the feedstock that is needed for the fuel production to the usage of the fuel in the vehicle to provide power to the wheels. Second, fuel pathways hardly have a comparable structure; they differ in number and complexity of processes. In a computer model for decision support about alternative fuels these different fuel paths have to be compared with each other. In order to make this possible the model has to be flexible to accommodate any kind of fuel path on the one hand, and provide a clear and unique structure in order to allow comparisons on the other hand. Finally, well-to-wheels pathways differ in environmental, economical, technical and social performance. For example, a well-to-wheels pathway that offers the biggest potential in reducing emissions might cause much more costs compared to another well-to-wheels pathway that creates much more emissions on the other hand. Furthermore the characteristics of the location also have an impact on the performance of the pathways. The well-to-wheels pathway with the biggest potential in reducing emissions in a certain city might show a totally different performance in another city that has different local conditions. Consequently there is no general “best” well-to-wheels pathway; the decision for or against a well-to-wheels pathway depends on the objectives of the decision maker on one hand, and on the local characteristics of the city on the other hand.

7

Introduction

1.4

Limitations

This thesis includes only the development of the structure of SUSI as a system for supporting decision makers in alternative fuels. Data input concerning alternative fuels is not subject of this thesis. SUSI does not intend to be a life cycle assessment tool. It does not aim for delivering accurate information about environmental impacts of well-to-wheels pathways. However, the outcome of SUSI shall cover the main contributors and therefore deliver comparable values that indicate the differing environmental impacts of the well-to-wheels pathways. It is important to keep in mind that the results that SUSI provides depend on the quality of the inputted data.

1.5

Methods

This thesis includes the development of a decision support system (DSS) about alternative fuels for decision makers in public transportation. In order to get a holistic picture about the subject of the DSS, the structure of alternative fuels, including environmental, economical, technical and socio-economic aspects were studied. Since this thesis is involved in the hydrogen fuel cell bus demonstration project ECTOS in Reykjavik, Iceland, this was done by means of the alternative fuel hydrogen. Methods applied were: ƒ

Literature review on alternative fuels

ƒ

Conference participation: Göteborg, May 26-27, 2004. Fuel Cells – Commercial possibilities for future applications6

ƒ

Conference participation: London, June 2004: 1st experiences of European Fuel Cell Bus Demonstration Projects7

ƒ

Site visit in Reykjavik, Interviews with the project coordinating company, representatives of bus and infrastructure operators, as well as with researchers

ƒ

Site visit in Stuttgart, Interview with local FC Bus operator

Second, after acquiring a holistic view about alternative fuels, for the implementation of the model SUSI the following methods were applied:

6

Conference Fuel Cells - Commercial possibilities and visions for future applications, Chalmers University of Technology, Göteborg, Sweden, 2004/05/26-27. 7 Conference First Experiences of European Fuel Cell Bus Demonstration Projects, London, 2004/06/14-15.

8

Introduction

ƒ

Literature review on database and DSS theory

ƒ

Site visit at IKP Stuttgart, Developer of LCA tool GaBi

ƒ

Conference participation: 2nd International Fuel Cell Bus Workshop, Porto, November 2004: Views on Data collection8

ƒ

Implementing SUSI with Microsoft Access 2002

Table 1 provides a list of interviews and site-visits conducted during the thesis process. Table 1: List of interviews Name

Company / Organisation & Position

Oskar Jonsson Maria Hildur Mack Gunnar Por Jonsson Mr. Petur Fenger & Steindur Steinposson Hjalti Pall Haukur Oskarsson Micheal Faltenbacher Steffen Raff

Topic dbase/DSS TFK development Data collection, project Icelandic New Energy - Environmental Manager organisation Data collection, Evobus - Bus Workshop Department Hydrogen Data collection, Bus Straeto - Operations Manager Operations Data collection, IceTec-Environmental Studies Environmental Studies Skeljungur hf. - Manager Constructions & Data collection, Technology Hydrogen Emissions Inventory IKP Stuttgart - Dept.Life Cycle Enineering, Calculation Project Manger Data collection, Bus SSB - Bus Workshop Department Operations

Location Date Borlänge,S June 2004 weden Reykjavik, October Iceland 2004 Reykjavik, October Iceland 2004 Reykjavik, October Iceland 2004 Reykjavik, October Iceland 2004 Reykjavik, October Iceland 2004 Stuttgart, November Germany 2004 Stuttgart, November 2004 Germany

Kristina Haraldson, Per Wilkström

KTH Stockholm - Energy Process Busslink i Sverige AB - Quality Dept.

Presentation of SUSI, suggestions for further work

Porto, Portugal

November 2004

L.Govaerts-L.Pelkmans, Shang Q. Hsiung, Leslie Eudy, Lisa Callaghan

Vito Belgium, Fed.Transport Adm.US-System Analyst, NREL US-Senior Project Leader, NAVC US-Project Coordinator

Presentation of SUSI, suggestions for further work

Porto, Portugal

November 2004

1.6

Disposition

The report is divided into five parts. Chapter 1 provided the background the thesis is based on, the aim, problem analysis, limitation and methods. Chapter 2 describes why hydrogen and fuel cells are a strategic option for the EU to cope with the challenges that arise from the transportation sector’s dependence on fossil resource based fuels. Next, the structure of a fuel supply path is analysed by means of hydrogen; hydrogen production methods and infrastructure issues are discussed.

8

Conference 2nd International Fuel Cell Bus Workshop, Porto, 2004/11/18-20.

9

Introduction

Chapter 3 introduces a theory review about methods for evaluating well-to-wheels pathways, decision factors in public transportation and databases as well as decision support systems. Chapter 4 presents the development of the model “Sustainable Urban Transport System Investigation” (SUSI v1.0) and provides the results by presenting an example how SUSI can support decision makers in public transportation. Chapter 5 provides the concluding remarks and recommendations for further development of SUSI.

10

Hydrogen and fuel cells

2

Hydrogen and fuel cells

This chapter gives an overview about the structure of a well-to-wheels pathway in order to understand the issues that have to be taken into account in the evaluation of alternative wellto-wheels pathways. This is done by means of hydrogen and fuel cells for two reasons. First, the development of SUSI is part of the fuel cell bus demonstration project ECTOS in Reykjavik, Iceland. Second, according to the policy of the EU hydrogen is the strategic fuel option for the EU to cope with the challenges that arise from the transportation sector’s dependence on fossil resource based fuels.

2.1

Why Hydrogen, why fuel cells?

To maintain economic prosperity and quality of life, Europe requires a sustainable energy system that meets the conflicting demands for increased supply and increased energy security, and at the same time reduces the impact on climate change, improves air quality and maintains cost-competitiveness. Hydrogen and fuel cells are strategic technologies to meet these objectives and to cope with these challenges (European Commission - DirectorateGeneral for Energy and Transport, 2003c).

Figure 6: Hydrogen – supply and demand9

2.1.1

Hydrogen

Hydrogen – H2 – is the most abundant chemical element on earth; nonetheless, it is hardly found in its energy-rich molecular state but mainly in chemical compounds like water and hydrocarbons (oil, natural gas, etc.). To produce hydrogen primary energy or electricity is

9

European Commission - Directorate-General for Energy and Transport: Hydrogen Energy and fuel cells: A vision of our future, Office for Official Publications of the European Communities. Luxemburg, 2003c.

11

Hydrogen and fuel cells

needed. The most common production paths are steam reforming of natural gas, partial oxidation of oil and water electrolysis (Figure 6). Hydrogen is not a primary energy source like coal and gas; it is an energy carrier like electricity. Hydrogen’s key advantage over electricity is the fact that it can be stored comparably easily. The storage problem of electricity hinders renewable energy sources to be integrated in the energy sector at large scale. The varying and intermittent nature of renewable sources like wind and solar energy constrains the power grids in securing a balance of supply and demand at any time. Hydrogen in use as an energy buffer can therefore facilitate large scale integration of renewable energy sources in the energy sector.

2.1.2

Fuel cells

Fuel cells can be used in a wide range of applications, ranging from very small fuel cells in portable devices such as mobile phones and laptops, through mobile applications like cars, trucks, buses and ships in the transportation sector, to heat and power generators in stationary applications in the domestic and industrial sector (Figure 7).

Figure 7: Fuel Cells - Fuels and applications10

Fuel cells can be powered by several fuels; there are very low to zero greenhouse gas emissions and emissions of air polluting substances. They offer high efficiencies that are independent of size and a high ratio of electricity to energy compared with conventional heat and power plants. Fuel cells are mechanically simple without any moving parts resulting in low vibration and noise as well as low maintenance requirements (European Commission Directorate-General for Energy and Transport, 2003c). There are several different types of fuel cells (PEM, AFC, DMFC, etc. view Figure 7) with in principle a similar functionality. 10

European Commission - Directorate-General for Energy and Transport: Hydrogen Energy and fuel cells: A vision of our future, Office for Official Publications of the European Communities. Luxemburg, 2003c.

12

Hydrogen and fuel cells

However they can differ in type of used materials and application. Figure 8 shows how a single PEM (Polymeric Exchange Membrane) fuel cell works, currently the most widespread type of fuel cell which is also used in the ECTOS, CUTE, STEP projects.

Figure 8: PEM fuel cell11

Unlike conventional engines, FC do not burn fuel or have any moving parts. FC convert hydrogen and air directly to electricity and heat through an electrochemical process. Thus they have fewer efficiency losses and no harmful emissions.

2.1.3

Benefits of hydrogen powered fuel cells

The benefits of hydrogen powered fuel cells are wide ranging. They can help to reduce energy imports since they have the flexibility to adapt to the diverse and intermittent renewable energy sources (European Commission - Directorate-General for Energy and Transport, 2003c). Since hydrogen is also well-suited as a vehicle fuel, it enables these renewable energy sources to be introduced into transport systems and therefore can be used as a substitute fuel to reduce the transportation sector’s dependence on oil (European Commission - DirectorateGeneral for Energy and Transport, 2003c). Besides reducing the dependency on external energy supply, hydrogen powered fuel cells also mitigate the effects of climate change and improve air quality. If renewable sources for hydrogen production are used, hydrogen powered fuel cells offer an energy production pathway that is almost completely free of CO2 emissions and other pollutions (European Commission - Directorate-General for Energy and Transport, 2003c). Finally, the challenge of economic ‘disruptions’ resulting from limited fossil fuel resources and unstable political conditions in the supply countries could be solved since hydrogen gives 11

h-tec. PEM fuel cell. www.h-tec.com/education/eng (2005-02-01)

13

Hydrogen and fuel cells

access to a broad range of primary energy sources including renewables. Availability and price of hydrogen should be more stable compared to the price for fossil fuels (European Commission - Directorate-General for Energy and Transport, 2003c). In brief, renewable-produced hydrogen in combination with fuel cells offers an effective strategy for significantly lowering greenhouse gas emissions and air pollution as well as improving fuel supply diversity to reduce economic disruptions and energy supply dependency.

2.1.4

Challenges for the hydrogen/fuel cell market introduction

The hydrogen/fuel cell technology is only at the beginning of its development but, because it is competing on the fuel market with mature technologies, like the gasoline/diesel internal combustion engine technology that is more than hundred years old and disposes of a widespread infrastructure, several challenges lie ahead (European Commission - DirectorateGeneral for Energy and Transport, 2003c). Cost Today fuel cells are generally too expensive for commercial introduction since they consist of expensive materials and are only produced in small scales. Fuel cell vehicles are not available at all on commercial markets; there are only a few prototypes running on the streets today, showing the general feasibility of the technology. Lifetime and reliability There are only little experiences about the lifetime and reliability of fuel cells and its supporting infrastructure; they still have to be proven. Novelty Any new technology requires significant support and public understanding in order to compete on a conservative market like the transportation fuel market. Infrastructure There is a lack of hydrogen/fuel cell supporting infrastructure. This includes refuelling sites, large scale manufacturing processes and support infrastructures like trained personnel. In the following section the hydrogen supply technologies and their status of development will be described in detail.

14

Hydrogen and fuel cells

2.2

Hydrogen production

Hydrogen can be derived by a multitude of production types using a wide range of primary and secondary energy carriers. Most of these production technologies are not yet fully available on commercial markets; some of them are just at the beginning of the development stage. Figure 9 gives a qualitative assessment of the present status of the hydrogen production technologies that are discussed more in detail in the following section.

Figure 9: Status of hydrogen production technologies12

2.2.1

Water-Electrolysis

Water-Electrolysis is the process of unpicking water molecules (H2O) into hydrogen (H2) and oxygen (O2) by means of electricity. This process takes place in a water electrolysis cell where an electric current flows between two electrodes in a water electrolyte. On the positive electrode (anode) gaseous oxygen is formed and gaseous hydrogen on the negative electrode (cathode). In this process no harmful emissions are produced. Figure 10 shows the mode of functioning of a water electrolyser. Hydrogen production from water electrolysis has many decades of industrial application. New developed units for on-site hydrogen production increase steadily their reliability making electrolysis based hydrogen filling stations for the supply of compressed gaseous hydrogen to road vehicles possible within the coming years (European Commission - Directorate-General for Joint Research Centre, 2004).

12

European Commission - Directorate-General for Joint Research Centre: Potential for Hydrogen as a Fuel for Transport in the Long Term (2020 - 2030), Office for Official Publications of the European Communities. Luxemburg, 2004.

15

Hydrogen and fuel cells

Figure 10: Mode of Functioning of a Water Electrolyser13

Feedstock Water electrolysis needs electricity as feedstock. Electricity is a secondary energy carrier that can be produced by all kinds of resources, fossil, renewable and nuclear. If renewable and nuclear resources are used, water electrolysis offers a hydrogen production path that is almost completely free of CO2 and other harmful emissions. There are many renewable resources for electricity production. Some of them are: ƒ

Wind power

ƒ

Solar power

ƒ

Geothermal power

ƒ

Biomass

ƒ

Etc.

If fossil resources are used for electricity generation the production pathway is not emission free. The level of emissions can vary a lot and depends on the used resource and production type. Fossil resources are: ƒ

Oil

ƒ

Coal

ƒ

Natural gas

2.2.2

Steam reforming

In the steam reforming process methane and water steam are converted to hydrogen. Figure 11 shows the process steps in detail.

13

Faltenbacher, M., et al.: CUTE - Clean Urban Transport for Europe - Hydrogen supply infrastructure and fuel cell technology. Ulm, 2004b.

16

Hydrogen and fuel cells

A mixture of the pre-treated water steam and methane passes through a heated chamber that contains a nickel catalyst. When the methane molecules hit the catalyst they split into CO and H2. The water vapour splits into H2 and O2 which combines with the CO that is produced in the first reaction into CO2. In this way very little CO is released as most of it is converted into CO2. The required heat is produced by burning parts of the input methane rich gas. Water

H2

Heat High Temperature Exchange Conversion

Purification

Feed Pre-Treatment

Cooling water

Reforming and Steam Generation

Air

Purge gas

Condensate

Figure 11: Mode of functioning of a steam reformer14

Steam reforming of natural gas in centralized large scale steam reformers is the most common process to produce hydrogen today. Small scale on-site steam reformers dedicated to produce the fuel for a hydrogen filling station have been developed by some companies and are already in use in demonstration projects, for example in the CUTE-project in Madrid and Stuttgart (European Commission - Directorate-General for Joint Research Centre, 2004). Feedstock Needed feedstocks for the steam reformer process are mainly a methane rich gas and water. A comparable little amount of electricity is also needed. The most common resource for the methane rich gas is natural gas. But also biogas is considered as a feedstock for steam reforming. This technology is still in the developing stage. Biogas is obtained via anaerobic digestion of organic waste or dedicated plantation, e.g. grass. Hydrogen from biomass can be produced in small and medium scale plants and is one of the most cost effective hydrogen production pathways with the benefit of being renewable. It has to be taken into account that although biogas is a renewable resource steam reforming contributes to the global warming by emitting the strong GHG N2O. The amount of N2O

14

Faltenbacher, M., et al.: CUTE - Clean Urban Transport for Europe - Hydrogen supply infrastructure and fuel cell technology. Ulm, 2004b.

17

Hydrogen and fuel cells

varies; it depends on the level of fertilizer input, climate and other factors (European Commission - Directorate-General for Joint Research Centre, 2004).

2.2.3

Partial oxidation of heavy hydrocarbons

The low volatility of heavy hydrocarbons like oil and its often high sulphur content makes it impossible to use steam reforming for the production of hydrogen. To produce hydrogen from heavy hydrocarbons partial oxidation can be used instead. The partial oxidation process treats the hydrocarbon autothermically in a combustion process reaction with reduced feed of oxygen at 1300-1500 °C. No water steam is added like it is the case in the steam reforming process. Thus, besides CO2 an additional by-product of this production method is CO (Kruse et al., 2002). Feedstock As feedstock for hydrogen production by partial oxidation any type of hydrocarbon comes into question. Since it is applicable also for heavy hydrocarbons like heavy oil, this procedure is often used in refineries where heavy oil is a by-product of the oil conditioning process and therefore is available for low cost. 25 % of the total hydrogen is produced in this way (Geitmann, 2004).

2.2.4

Autothermal reforming

The autothermal reforming process is a combination of steam reforming and partial oxidation, in which the needed heat energy for the reforming of hydrocarbons is produced automatically. Therefore this method is named “autothermal”. By controlling the amount of oxygen for the combustion process, the produced heat is exactly the heat needed for the reforming process. In this way the energy recovery can be increased considerable. On the other hand emissions of nitrogen oxides are significantly higher (Geitmann, 2004). Feedstock As for partial oxidation any kind of hydrocarbon can be used as feedstock for autothermal reforming.

2.2.5

Gasification

In the gasification process solid hydrocarbons like coal or heavy fuel oil are heated up to more than 900 °C with a catalyser to a synthesis gas. After cooling down H2 is separated from soot and solid particles (Geitmann, 2004). 18

Hydrogen and fuel cells

Feedstock Besides the fossil fuels coal and heavy fuel oil, the renewable source biomass is getting more and more interesting. Especially waste wood in forestry and wood-working industry feedstock lends itself to biomass gasification.

2.2.6

CB&H Process (Kværner)

In the CB&H process (carbon black and hydrogen) hydrocarbons (e.g. natural gas, heavy fuel oil) are converted into hydrogen and carbon black by using a plasma torch implemented in a high temperature reactor to pyrolyze the hydrocarbon feedstock. Carbon black is super pure carbon which is used in car tyre production and metallurgic industries. The technology was developed by the Norwegian Kværner Engineering S.A. since the beginning of the 80ies. In this process which needs electricity as feedstock but no oxygen, no relevant emissions crop up. A by-product is hot steam. Under the precondition that there is a use for all by-products this process offers almost 100% energy efficiency from which about 50% counts to hydrogen, 40% to coal black and 10% to heat. Compared to other fossil fuel based hydrogen production processes the CB&H process has the advantage that there are no CO2 emissions if renewable electricity is used (Geitmann, 2004). Feedstock The process needs two types of feedstock: hydrocarbons and electricity. Since it is possible to use a wide range of hydrocarbons the CB&H process offers vast feedstock flexibility.

2.2.7

Thermochemical cycles

Above the temperature of 4.000 °C the break-up of water into hydrogen and oxygen takes place. The direct thermal steam dissociation requires highly heat-resistant materials what makes it not feasible economically. Thermochemical cycles are the coupling of two or more balance reactions which allows reducing the temperature to 1.000 to 1.700 °C by adding iodine and sulfur dioxide. The emerging gases hydrogen and oxygen are separated by ceramic membranes that are diaphanous for hydrogen but not for oxygen (Geitmann, 2004), (European Commission - Directorate-General for Joint Research Centre, 2004). Feedstock Required feedstock is high temperature heat that is produced either by nuclear power or direct solar radiation.

19

Hydrogen and fuel cells

2.2.8

Photo-electrochemical production

Instead of converting sunlight into electricity and then using an electrolyser to produce hydrogen from water, it is possible to combine these two functions. The photovoltaic cell is combined with a catalyser which acts as an electrolyser and splits hydrogen and oxygen directly from the surface of the cell (Kruse et al., 2002). The drawback in directly producing hydrogen is that oxygen is produced at the same time with both gases mixed at the outlet of the installation. This increases the complexity of the installation as the gases have to be separated, and it is an important safety risk as the gas mixture is explosive (European Commission - Directorate-General for Joint Research Centre, 2004). Photo-electrochemical hydrogen production is still in the stage of basic research. Feedstock The only feedstock needed for this technology is water which is usually easy available at every location. Therefore feedstock supply causes only very little costs and environmental impacts. Of course this production pathway requires certain climate conditions that ensure stable sun radiation in order to be efficient.

2.2.9

Biological production

Biological water electrolysis (splitting water into hydrogen and oxygen) is the first step in photosynthesis that occurs when in the cells of plants chlorophyll absorbs sunlight. Enzymes use this energy to break water down into hydrogen and oxygen. The hydrogen is then combined with CO2 into carbohydrate. Photo biological production of hydrogen aims to recover the hydrogen which is released within this dissociation process. Special algae allow the separate collection of hydrogen and oxygen under certain conditions. Under laboratory conditions it was possible to produce 250 millilitres per day out of 1 litre algae what would be enough to supply a one-family house with energy. Beside photo biological production, hydrogen can also be produced by bacteria from organic waste like fruit and vegetables and has also been tested on sewage with positive results (Kruse et al., 2002). Biological hydrogen production is in both cases still in the phase of basic research.

20

Hydrogen and fuel cells

2.2.10

Hydrogen as a by-product

In chlorine gas production by electrolysis, hydrogen is generated as a by-product. Since the late 19th century Chlorine (Cl2) production has increased significantly on world-scale and has reached a level of approx. 35 million tons per year. 95% of all chlorine is produced in electrolysis processes with hydrogen as a by-product. By definition, by-product hydrogen is limited in quantity and does not have well-defined production costs. Supply prices of by-product hydrogen will depend on the market situation. Consequently by-product hydrogen is one of the cheapest hydrogen supply pathways at present, cheaper than steam reforming of natural gas (European Commission - DirectorateGeneral for Joint Research Centre, 2004).

2.2.11

Summary

Hydrogen can be produced by a wide range of methods requiring a wide range of feedstock which again can be derived from a wide range of resources. The availability and efficiency of these production methods often depends on the location, as availability of resources and climate conditions and other characteristics differ from region to region.

An overview about possible fuel supply paths which are at least in the stage of process validation is shown in Table 2. Production methods that are in the stage of basic research are not included, since it is likely that they will not be available in a medium time horizon.

21

Hydrogen and fuel cells

Table 2: Hydrogen production methods, feedstock and resources Production Method Water Electrolysis

Steam reforming

Partial Oxidation Autothermal reforming

Gasification

CB&H Process

By-product

Feedstock Electricity

Resource Oil Coal Natural Gas Uranium Wind Solar radiation Geothermal heat Hydrostatic energy organic waste dedicated plantation Methane rich gas Natural Gas Organic waste Dedicated plantation Heavy Hydrocarbons Oil Coal Methane rich gas Natural Gas Organic waste Dedicated plantation Heavy Hydrocarbons Oil Coal Heavy Hydrocarbons Oil Coal Biomass Organic waste Dedicated plantation Electricity Oil Coal Natural Gas Uranium Wind Solar radiation Geothermal heat Hydrostatic energy organic waste dedicated plantation Methane rich gas Natural Gas Organic waste Dedicated plantation Heavy Hydrocarbons Oil Coal Chemical industry processes

2.3

Hydrogen infrastructure

2.3.1

Hydrogen storage

Hydrogen can be stored in small or large quantities using a variety of different storage methods, such as gaseous or liquid hydrogen storage, or physically or chemically bound to the storage material (European Commission - Directorate-General for Joint Research Centre, 2004). Figure 12 provides an overview about research on hydrogen storage systems. The stationary storage is common practice in the chemical industry, where it works safely and provides the service required. However, storage systems for mobile applications that offer driving ranges comparable to diesel or gasoline vehicles are still in the research and development stage requiring further evaluation. Conventional onboard hydrogen storage systems such as compressed gas cylinders and liquid tanks can be lighter, stronger and cheaper and therefore offer the potential to meet the requirements to be used for vehicle applications (European Commission - Directorate-General for Energy and Transport, 2003c), as well as metal 22

Hydrogen and fuel cells

hydrides and adsorption in carbon structures. Furthermore completely new innovative technologies which cannot be foreseen yet could offer new storage possibilities (European Commission - Directorate-General for Joint Research Centre, 2004). In the following section current hydrogen storage systems for hydrogen distribution and vehicle onboard storage are described more in detail.

Figure 12: Status of hydrogen storage technologies15

Compressed gas cylinders Since hydrogen is gaseous in ambient air temperature it is self-evident to use gaseous storage, too. According to the thermodynamic laws the volume of gases can be reduced by increasing the pressure. Suitable tanks for compressed gaseous hydrogen storage (CGH2) are steel cylinders. For mobile applications hydrogen is stored at pressures between 200 and 350 bar (Geitmann, 2004). This technology is well understood and generally available since it has already been used for the storage of natural gas (European Commission - Directorate-General for Energy and Transport, 2003c). A pressure of 350 bars is regarded sufficient for most city bus and urban vehicle applications. Due to increased requirements in operating range and consumer space, passenger cars require bigger storage capacities of smaller size. 700 bars storage system would meet these requirements and are currently under development (European Commission - Directorate-General for Joint Research Centre, 2004).

15

European Commission - Directorate-General for Joint Research Centre: Potential for Hydrogen as a Fuel for Transport in the Long Term (2020 - 2030), Office for Official Publications of the European Communities. Luxemburg, 2004.

23

Hydrogen and fuel cells

Liquid tanks Another way to increase the storage density is to cool hydrogen down under its boiling point of about -253 °C and store it in liquid tanks (LH2). Although this is a well-understood technology which offers a good storage density there are several barriers. There are losses of hydrogen due to hydrogen evaporation caused by heat insertion into the liquid storage tank. These evaporation losses cannot be eliminated but minimized by using advanced insulation materials, making this storage technology comparable expensive. Furthermore the required low temperatures make the hydrogen liquefaction very energy intensive; approximately 30 to 40% of the energy content of the fuel is needed (Kruse et al., 2002). Liquid hydrogen storage has been used in aviation and is the most frequently used type of fuel storage in space travel. In road vehicles there are only prototypes used in demonstration projects until now (Kruse et al., 2002). Metal hydrides A hydride is a compound that contains hydrogen and one or more other elements. When hydrogen is pressed into a metal hydride tank it absorbs the hydrogen and releases heat. To discharge hydrogen from the granular metal, heat has to be applied. The required heat can generally be taken from the heat the fuel cell releases in operation (Kruse et al., 2002). Metal hydrides show very high volumetric storage densities but are very heavy. Metals that show a high storage density (hydrogen capacity per weight) such as magnesium-hydride require a too high desorption temperature (300 °C) to be handled in vehicle applications. On the other hand, there are hydrides that have a desorption temperature only slightly above ambient air temperature such as titan-hydride, but that are at the same time up to 25 times heavier and 25 times more volumetric than a filled gasoline tank (Geitmann, 2004). In brief, hydrogen storage in metal hydrides is an available technology offering in general good storage densities in a safe way. There is ongoing research on finding suitable materials to make this technology manageable for vehicle applications. Chemical hydrides Chemical hydride slurry is a safe, highly energy dense and easily handled hydrogen storage medium. Slurry is a mixture of a solid and a liquid to make a pumpable mixture. When hydrogen is needed, the chemical hydride slurry is mixed with water. The chemical reaction of the water with the chemical hydride produces hydrogen. Heat and a hydroxide of the 24

Hydrogen and fuel cells

original hydride are by-products (McClaine et al., 2004). One example for a chemical hydride is boron-hydride. Challenges lie in the handling of the hydroxide which needs to be recycled and therefore requires a reverse logistics infrastructure (European Commission - DirectorateGeneral for Energy and Transport, 2003c). Activated Carbon structures The chemical element carbon can assume several different structures showing different characteristics what becomes obvious considering the hard diamante and the soft graphite. Another carbon structure is the 1991 discovered nanotube which has a hexagonal atomic structure allowing the absorption of hydrogen atoms (Geitmann, 2004). This technology has just been discovered and is in the basic research stage. It may allow a high storage density at low weight and low cost. But since this technology is not fully understood and developed, early promises remain unfulfilled until now.

2.3.2

Hydrogen distribution and conditioning

The hydrogen production technologies deliver usually gaseous hydrogen of low pressure making the handling very difficult. Before it can be distributed to the sites, hydrogen can be conditioned and distributed in different ways that are described in detail in this section. Figure 13 gives a qualitative assessment of the present status of hydrogen distribution and conditioning technologies.

Figure 13: Status of hydrogen distribution and conditioning technologies16

Gaseous hydrogen Gaseous hydrogen can be transported in pressurized bottles, in tube trailers and in pipelines. Steel bottles have more than 50 years of industrial experiences with excellent safety records 16

European Commission - Directorate-General for Joint Research Centre: Potential for Hydrogen as a Fuel for Transport in the Long Term (2020 - 2030), Office for Official Publications of the European Communities. Luxemburg, 2004.

25

Hydrogen and fuel cells

as well as composite materials bottles at 30 MPa that are in service since about 10 years. However, one trailer can transport only up to 6,000 Nm³ CGH2. This results in low energy efficiency which limits the use of trailer transport to short distances of about 200 km (Geitmann, 2004). The compression of hydrogen is achieved by use of piston, diaphragm and hydraulic compression. The suction pressures lie between 0.1 and about 3 MPa, the delivery pressures up to 120 MPa depending on the type of application. The electric power requirements depend on the pressure delivered. At a suction pressure of about 3 MPa the power need drops significantly (European Commission - Directorate-General for Joint Research Centre, 2004). Liquid hydrogen Hydrogen can also be transported in liquid condition with the advantage of higher hydrogen capacities. A LH2 trailer can transport about 5 times the hydrogen amount of a CGH2 trailer. This enables LH2 to be delivered to a refuelling station by trailer transport comparable to today’s delivery of liquid hydrocarbon vehicle fuels (European Commission - DirectorateGeneral for Joint Research Centre, 2004). In order to use liquid transport hydrogen needs to be liquefied. Hydrogen liquefaction is an industrial technology since the 1960s when in the US liquefiers were built for the space program to supply the spaceships that used liquid hydrogen as fuel (European Commission Directorate-General for Joint Research Centre, 2004). Because of the high energy density, LH2 transport is also an option for intercontinental transportation. In the course of the “EuroQuebec Hydro-Hydrogen Pilot Project” (EQHHPP) container vessels have been developed in order to transport hydrogen from Canada to Europe. Hydrogen production and liquefaction can be done in Canada for comparable low cost due to cheap electricity produced in hydro power plants (Geitmann, 2004). Since hydrogen has to be cooled down below 253 °C this technology requires a considerable amount of electric energy. Pipeline system Pipeline transport for gaseous hydrogen has been performed over distances of up to 300 km for many decades mainly in the chemical industry. It is the appropriate transport method for large volumes at high utilization rates. Compared to natural gas pipeline transport for hydrogen is approximately a 3.5 times higher compression energy required to transport the

26

Hydrogen and fuel cells

same energy equivalent (European Commission - Directorate-General for Energy and Transport, 2003b).

2.3.3

Hydrogen filling stations

Filling stations link the fuel production and distribution with the vehicle. A dense network of filling stations is necessary in order to establish a mass market for hydrogen as a fuel (Geitmann, 2004).

Figure 14: Status of hydrogen filling station technologies17

Of the approximately 70 hydrogen filling stations operating worldwide the majority dispenses CGH2 (57) from which in 11 CGH2 is obtained from LH via evaporation and compression (LCGH2). Only 11 stations dispense LH2. This is due to the fact that most prototype vehicles use a CGH2 onboard storage system. Hydrogen can be provided to the filling station either by LH2 or CGH2 trailers, by pipeline system or by onsite-production. Onsite generation allows a completely new fuel pathway which does not require access to any existing ‘upstream businesses’ as today for hydrocarbon fuels. Independent fuel provider can purchase natural gas or electricity as basic input for hydrogen production and dispense hydrogen to its clients. This opens the sector for new players and provides new business opportunities (European Commission - Directorate-General for Joint Research Centre, 2004). Figure 14 gives a qualitative assessment of the present status of hydrogen filling station technologies.

17

European Commission - Directorate-General for Joint Research Centre: Potential for Hydrogen as a Fuel for Transport in the Long Term (2020 - 2030), Office for Official Publications of the European Communities. Luxemburg, 2004.

27

Theory

3

Theory

Well-to-wheels pathways differ in their technical, economical, environmental and socioeconomic performance. Thus, there is no general “best” fuel; it depends on the decision maker’s goals which well-to-wheels pathway is a good option for a certain location. Although the end use of the fuel in the vehicle has attracted the main attention, the performance characteristics of a well-to-wheels pathway not only depend on the “combustion” process of the fuel in the motor, but also when the fuel is produced, when the cars are manufactured and when roads are build, etc. In order to get a complete picture the whole system has to be analysed (Blinge, 1998). Therefore it is necessary to evaluate the well-to-wheels pathway in its entirety and over its complete life cycle in order to guarantee that the decision maker’s set of goals is reached (Faltenbacher et al., 2004a). The purpose of this chapter is to give an overview over the theory of methods for the evaluation of alternative fuel systems (3.1), of factors influencing the decision making on alternative fuel systems (3.2) and of decision support systems and databases (3.3).

3.1

Well-to-wheels pathway evaluation methods

3.1.1

Live Cycle Assessment (LCA)

A Life Cycle Assessment is defined in Baumann et al. (2004) as: In a live cycle assessment (LCA) a product or service is followed from its “cradle” where raw materials are extracted from natural resources, through production and use to its “grave”, the disposal. In Guinée et al. (2001) it is defined as: In ISO 14040 LCA is defined as the “compilation and evaluation of the inputs, outputs and potential environmental impacts of a product system throughout its life cycle.” Thus, LCA is a tool for the analysis of the environmental burden of products and services at all stages of their life cycle – from the extraction of resources, through the production of materials, product parts and the product itself, and the use of the product to the management after it is discarded, either by reuse, recycling or final disposal (in effect therefore “from the cradle to the grave”).

28

Theory

Figure 15: ISO 14040 LCA framework18

Figure 15 presents the framework of an LCA according to ISO 14040 standards. It consists of the definition of goal and scope, the life cycle inventory, the impact assessment and interpretation of results. This framework refers to all kinds of products and services. In environmental life cycle assessments, natural resource use and pollutant emissions are described in quantitative terms (Baumann et al., 2004). According to the international standard for LCA one application of LCAs is decision making, e.g. for product or process design and development. Furthermore it is used for learning/exploration, e.g. identification of improvement possibilities and communication purposes, such as LCA-based eco-labelling or benchmarking. The LCA software tool GaBi 4 The GaBi 4 (“Ganzheitliche Bilanzierung”) software system was developed by the Institute for Polymer Testing and Polymer Sciences (IKP) of the University of Stuttgart in collaboration with PE Europe GmbH, Leinfelden-Echterdingen. It is a software tool for comprehensive balances of products, services and systems to assess their technical, economic, environmental

and

socio-economic

impacts

(Institut

für

Kunststoffprüfung

und

Kunststoffkunde, 2003). GaBi was used to analyse the environmental impact of the different types of hydrogen supply infrastructures used in the CUTE, ECTOS and STEP projects. Figure 16 presents an example 18

Guinée, J. B., et al.: Life Cycle Assessment - An Operational Guide to the ISO Standards, Ministry of Housing, Spatial Planning and the Environment (VROM) Centre of Environmental Science - Leiden University (CML). Leiden, 2001.

29

Theory

of the LCA of the FC bus system as it was done in the projects for the on-site steam reforming and on-site electrolysis.

System Boundary Figure 16: LCA of a FC Bus System including system boundaries19

The FC bus system consists of four basic steps that are represented by four process chains consisting of Resources, Production, Operation/Use Phase and End of Life. The 1st column illustrates the processes for the sourcing of natural gas, the 2nd the sourcing of electricity. Natural gas and electricity are the feedstock for hydrogen production by on-site electrolysis and steam reforming respectively, whose processes are shown in column 3. The last column provides the processes of the FC bus. As indicated by the system boundary line, the FC bus is not included in this LCA, since for FC buses, which are near to emission free, potentially occurring emissions are shifted from the bus operation to the fuel supply. GaBi uses the LCA methodology as standardised in the ISO 14040. Every step of the life cycle is analysed by accounting its material and energy flows, resulting in an inventory of inand outputs of many different substances covering the analysed system “from cradle to grave” (Inventory Analysis). In order to assess the environmental impact of, for example, emissions to air, water or soil, the emissions are aggregated according to their impact in so-called impact categories (e.g. Global Warming Potential, GWP or Acidification Potential, AP) (Impact Assessment).

19

Faltenbacher, M., et al. Conference Internationaler Deutscher Wasserstoff Energietag 2004, Essen, 2004-0211.

30

Theory

3.1.2

Well-to-Wheels Analysis (WtW)

M. P. Hekkert (Hekkert et al., 2003) defines a Well-to-Wheels Analysis as follows: In this approach all life cycle steps of the fuel chains are analysed in terms of energy use and related carbon emissions. In fact, the approach is a comparative life cycle assessment of fuel chains but only focusing at energy requirements and carbon emissions. The name well-towheel stems from the fact that carbon emissions are taken into account that originate from a crude oil or gas well till the combustion emissions from a vehicle to produce wheel power. A comprehensive LCA of fuel systems should also investigate the production and the end-use of the fuel supply infrastructure and of the vehicles. According to Schindler (2003) this is usually not done in a WtW analysis due to the difficulty of data collection and the presumption that the effects of the fuel supply infrastructure and vehicles are of minor importance for the total WtW path. Activities related to building vehicles and infrastructures, such as manufacturing plants, filling station, roads, and equipment as well as the treatment after the end of the vehicle’s and infrastructure’s life are not considered. A WtW analysis can be split into a “Well-to-Tank” (WtT) stage and a “Tank-to-Wheel” (TtW). The WtT stage covers the fuel supply stage. It analyses the process of producing, transporting, manufacturing and distributing of the final fuel. This so called fuel path is the combination of necessary steps to convert a resource into a fuel and bring that fuel to a vehicle tank (European Commission - Directorate-General for Joint Research Centre et al., 2003). The TtW stage covers the use of the fuel in the vehicle. It analyses the energy consumption and emissions during the operation of a vehicle on a reference driving cycle (European Commission - Directorate-General for Joint Research Centre et al., 2003). The WtT analysis is described by successive processes that are required to convert resources to a final fuel and make it available to the vehicles (Figure 17). ƒ

Production and conditioning

This step includes all processes that are required to extract, cultivate or capture the resources as well as the conditioning at the source to make their transportation convenient, economical and safe. ƒ

Transformation

These processes are major industrial processes to transform resources to a fuel. They can take place both near the source of the resource and/or near the market of the fuel. 31

Theory

ƒ

Transportation

This step includes the transportation of the resources or the fuel to the market ƒ

Conditioning and distribution

Here are the final steps covered that are necessary to distribute the fuel from the point of import to the individual refuelling points. Also necessary conditioning steps like compression of gaseous fuels are included.

Figure 17: Concept of WtT analysis of the European WtW study20

Many of the processes are common for several pathways. A process is described by the energy expended and the amount of emissions for processing one energy unit of the final fuel. The energy consumed and emissions of a WtT path are calculated by summing up the values of each process of the WtT path. A software tool to conduct a well-to-wheel analysis is the GREET model which is described in the following section. GREET-Model The “Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model”, developed since 1995 by Argonne National Laboratory, Argonne USA, is an analytical tool for use by researchers and practitioners to estimate WtW energy use and emissions of transportation fuels and advanced technology vehicles (Wang, 2002). Figure 18 depicts the concept of the GREET WtW analysis. It includes three stages: Feedstock, fuel and vehicle operation. The fuel production covering feedstock- and fuel stages is called “well-to-pump”; the vehicle operation stage is called “pump-to-wheel”. The vehicle refuelling process is therefore the border between the two main stages; it is included in the vehicle operation. With this tool it is possible to calculate the WtW energy use and emissions of fuel paths that are predefined. The user is able to change parameters in order to get accurate data for his special case. Direct comparisons with other fuel paths or classifications according to certain impact categories or decision factors are not possible. 20

European Commission - Directorate-General for Joint Research Centre, et al.: Well-to-wheels analysis of future automotive fuels and powertrains in the European context, Office for Official Publications of the European Communities. Luxemburg, 2003.

32

Theory

Figure 18: GREET fuel cycle concept21

Well-to-Wheels case studies ƒ

EU Well-to-Wheels study

The study “Well-to-Wheels analysis of future automotive fuels and powertrains in the European context” by European Commission - Directorate-General for Joint Research Centre et al. (2003) evaluated the Well-to-Wheels energy use and GHG emissions for a wide range of potential future fuel and powertrain options under European average conditions. ƒ

GM Well-to-Wheels study

The study “Well-to-Wheel Energy Use and Greenhouse Gas Emissions of Advanced Well-towheels Systems – North American Analysis” (General Motors Corporation et al., 2001) evaluates a wide range of fuel paths taking average North American conditions into account. One year later the similar study “GM Well-to-Wheels Analysis of Energy Use and Greenhouse Gas Emissions of Advanced Well-to-wheels Systems – A European Study” (General Motors Corporation, 2002) was published considering European average conditions.

3.1.3

Summary of WtW pathway evaluation methods

The LCA framework provides a methodology for evaluating the environmental burden of products and services. It possesses a flexible structure that can be used to evaluate well-towheels pathways as well. There are software tools for conducting LCAs, from which GaBi is one of them, to calculate energy use, emissions and any other user-defined parameter in an accurate way. Applications of an LCA are e.g. decision making in product design and development, learning/exploration for identification of improvement possibilities and communication of LCA based eco-labelling.

21

Wang, M. Q.: Development and Use of GREET 1.6 Fuel-Cycle Model for Transportation Fuels and Vehicle Technologies, Center for Transportation Research, Energy Systems Division, Argonne National Laboratory. Argonne, 2001.

33

Theory

The Well-to-Wheel analysis is somehow an application of the LCA methodology for fuels with predefined boundaries and only focusing at energy requirements and GHG emissions. The purpose of a WtW is to learn about and to explore the environmental impact of well-towheels pathways in order to examine improvement possibilities or to support decision making about the design of a public transportation system. The GREET model is a tool to calculate WtW emissions of well-to-wheels pathways. The WtW studies conducted by the EU and GM provide the energy use and GHG emissions of a wide range of fuel paths. By this they become comparable and offer a comprehensive basis to take decisions. On the other hand the results are based on many assumptions representing average figures. Especially key parameters like the configuration of the electricity grid mix or the origin of resources for the fuel production like natural gas, which influence the results of the whole WtW path considerably, differ to a great extend from location to location. Thus, the results presented in the WtW studies are in some cases of limited value, since these key parameters deviate from the average conditions.

3.2

Decision factors for alternative fuels

When creating a model for the support of decision making it is necessary to have a comprehensive picture about the factors that build the basis for the decision. In the case of alternative fuels there are plenty of these factors. They vary between different groups of decision makers but it can be assumed that several of these factors are the same for most of the decision makers. These factors were evaluated by a Swedish project called MUD (Ottosson, 2004).

3.2.1

MUD evaluation

Two seminars were held with two groups of decision makers, local transport governments and politicians from different parts of Sweden. In total approximately a third of Sweden’s geographical traffic areas has been interviewed. Interviews have been made with politicians from regional as well as local level and city areas as well as countryside areas. The result was that there is a need for a model of limited complexity that supports decision making about alternative fuels. The model should focus on finding out which alternative fuel can fulfil the following criteria in the long term:

34

ƒ

Environmental impact

ƒ

Long term access

Theory

ƒ

Public attitude

ƒ

Reliability

ƒ

Total economics

These criteria are presented more in detail in the following section.

3.2.2

Environmental impact

According to Ottosson (2004) the emissions from using the alternative fuel shall have a small local and regional environmental impact and as far as possible no global impact. Figure 19 presents the different impact categories and their impact levels. This section provides a detailed overview about these categories. Geographical level

Global Climate change

Regional Eutrophication Acidification

Local Photochemical Ozone Creation Human Ecotoxicity

Time

Figure 19: Local, regional and global impact categories22

Climate change Without the natural greenhouse effect the earth’s temperature would be much lower than it is now and life as it is would not be possible. Atmospheric greenhouse gases trap some of the outgoing energy and retain heat and determine the earth’s climate in this way. Burning fossil fuels increases the level of atmospheric greenhouse gases, mainly CO2, CH4 and N2O on a global scale, and thus strengthens the natural greenhouse effect and rises global temperature. The global warming triggers for example desert expanding, raising sea levels, etc. and influence the world’s climate affecting human health and ecosystems (TFK Transport Research Institute, 1998). Eutrophication On a regional scale eutrophication covers the impact of nutrients, mainly caused by the emission of the gas NOx. Nutrient enrichment may cause a shift in species composition, and 22

Lecture Magnus Blinge in the course “Environmental Aspects on Logistics and Transportation”

35

Theory

elevated biomass production in both, water and terrestrial ecosystems. In addition, high nutrient concentrations may also render surface waters unacceptable as a source of drinking water. In water ecosystems increased biomass production may lead to smaller oxygen levels, because of the additional consumption of oxygen in biomass decomposition (Guinée et al., 2001). Acidification Acidification is caused by emissions on regional scale. The major acidification pollutants are SO2 and NOx. They combine with other molecules in the air into acid. Acidification pollutants have a wide variety on soil, groundwater, surface waters, biological organisms, ecosystems and materials (buildings). Examples include fish mortality in Scandinavian lakes, forest decline and the crumbling of building materials (Guinée et al., 2001). Photochemical Ozone Creation The ozone layer in the upper atmosphere is a necessary protection against the UV radiation from the sun. At ground levels, on the other hand, ozone is dangerous for people, animals and plants (TFK Transport Research Institute, 1998). Photochemical ozone creation, also known as summer smog, is the formation of the reactive chemical compound ozone by the action of sunlight on certain primary air pollutants. Ozone is injurious to human health end ecosystems and may also damage crops. Ground level ozone is formed in the atmosphere under the influence of ultraviolet light of the solar radiation through photochemical oxidation of Volatile Organic Compounds (VOCs) and carbon monoxides (CO) in the presence of nitrogen oxides (NOx). The ozone formation takes place on local scale and will vary in different regions and at different times as a result of varying background concentrations and sun-intensities. Ozone causes bronchial irritation, coughing, etc. (Guinée et al., 2001). Health problems Human being exposure to toxic substances through air, water, soil or through the food chain can cause serious health problems. Traffic gives rise to emissions of a number of these substances. This is caused on a local level mainly by volatile organic hydrocarbons (VOC), emitted by ICE and during fuel production, and particles that are emitted mainly by diesel engines and are probably the most dangerous type of emissions. These substances are carrier of cancer inducing compounds and irritate lungs, throat and eyes. Furthermore SO2, NOx, CO as well as noise affect human health (TFK Transport Research Institute, 1998). 36

Theory

Summary Emissions from road transport activities contribute to climate change, acidification, Eutrophication, ozone at ground level and cause health problems. Table 3: Road transportation emissions and environmental impact categories23 Emission

Climate change

Acidification

Carbon Dioxide

CO2

X

Methane

CH4

X

Nitrous oxide

N2O

X

Nitrogen oxides

NOx

X

Sulphur dioxide

SO2

X

Volatile Organic compounds

VOC

Particles

PM

Carbon Monoxide

CO

Eutrophication

Ozone at ground level

X

X

X

X

X

X

X

X X

X

Noise

3.2.3

Human health

X X

Long term access

Besides economical and ecological impacts of an alternative fuel, the long term access to the fuel and its raw materials is also of importance for the decision makers. The access to a fuel is determined by two issues. First, the access is endangered if a fuel can only be accessed from a few regions worldwide. Particularly in the case of unstable political circumstances in these regions, continuous fuel supply can not be taken for granted (European Commission - Directorate-General for Energy and Transport, 2003c). Second, there is a natural limitation of the access to a fuel. A fuel produced from resources that are not renewable, will inescapably lead to depletion of the resource in question, resulting to the incapability of producing the fuel (European Commission - Directorate-General for Energy and Transport, 2002b). Long term access therefore goes close together with the non-renewable resource consumption, meaning in the first instance oil on which almost the entire transport sector’s fuel is based on. The fact that a significant part is produced in political unstable middle-east countries, together with depleting oil reserves renders oil based fuels not long term accessible. 23

TFK Transport Research Institute: Environmental Handbook for Transport Purchasing, TFK Transport Research Institute. Stockholm, 1998.

37

Theory

Renewable sources are by definition not depleting, so there is no danger of running out of resources for the fuel production. Furthermore, the great variety of renewable energy sources makes them applicable to many regions worldwide. Supply shortages caused by political irritations have therefore not to be assumed.

3.2.4

Public attitude

The choice of alternative fuel should be in line with the public attitude (Ottosson, 2004). This includes the acceptance of the alternative fuel usage scheme. The main factors that influence the public attitude are the level that passengers have to change their behavioural patterns and safety issues concerning the usage of alternative fuels.

3.2.5

Reliability

Another requirement for an alternative fuel is its reliability that has to be in parity with the use of today’s conventional fuel. Reliability in public transportation represents the percentage of the out-of-service time of a bus from the total planned service time. A bus can not only be out of service due to bus-related problems, but also because of infrastructure failures, e.g. insufficient fuel supply. Thus, the total system has to be considered. There are many ways to measure the reliability; an accepted standard definition among public transport providers does not exist24. Even if a common definition could be found, differing parameters from location to location, such as total service time, local traffic conditions or topography, make it difficult to compare similar fuel systems, not to mention a comparison of different ones.

3.2.6

Total economics

The best fuel options from an environmental, reliability or public attitude point of view are only probable to raise attention for decision makers if they can be developed at a reasonable cost (European Commission - Directorate-General for Joint Research Centre et al., 2003). Nevertheless, cost estimations are filled with difficulties, particularly when it comes to processes, systems and vehicles that do not yet exist at any remarkable scale. A definite analysis is not possible but still, indicative costs for the ownership and operation of an alternative fuel system can provide an insight of the total costs of various options (European Commission - Directorate-General for Joint Research Centre et al., 2003). These indicative

24

Conference 2nd International Fuel Cell Bus Workshop, Porto, 2004/11/18-20.

38

Theory

costs include fuel cost, vehicle cost and the cost for the infrastructure in a reasonable time horizon (Ottosson, 2004).

3.3

Decision support systems and databases

In the following section the theory concerning the development of the Decision Support System (DSS) model and the dbase is presented in brief. Although the bibliography concerning the topic is vast, only the theoretical background that was used for this thesis will be presented; thus the sections concerning the DSS theory and dbase theory aim to explain the approaches that were used for the DSS and dbase development.

3.3.1

Decision support system

A DSS is a compilation of tools aiding the process of decision making. The concept of DSS evolved in the 70s and 80s; when the main theoretical background was set and categorisation of the systems was made. Although still the concept of DSS is rather general and vague the following definition is generally accepted; an interactive computer based system, which helps decision makers utilize data and models to solve unstructured problems (Sprague et al., 1993). Even though the use of DSSs has received much greater attention concerning business and economic applications, DSSs in environmental research commenced in parallel with the use of the systems in the business and economic area. Environmental problems and the process of reaching decisions are in most cases far more complicated than business problems, since technical, social, and economic factors should be considered (Jolma, 1995). In 1977, S. Alter proposed a taxonomy of DSS according to which there are seven categories of DSS; SUSI fits best into the description of two out of the seven categories: file drawer system and optimization model; file drawer system: provides access to data, and optimization model: provides guidelines for action by generating an optimal solution consistent with a series of constraints (Alter, 1977), (Power, 2002). According to (Hogue, 1987) there are four parties that play a role in producing a DSS: ƒ

approver and administrator which is the coordinator of the development and usually the party that finances the DSS development,

ƒ

developer: the person or group of persons providing the technical background for the development of the DSS 39

Theory

ƒ

operator: the person or group of persons operating the system and keeping it up to date

ƒ

user of output: the actual person or organisation that will use the support of the DSS.

According to Sprague et al. (1993) all DSS have three basic components: ƒ

Dialog Component

ƒ

Data Component

ƒ

Model Component.

Figure 20 describes the relationships between the basic components and the user of a DSS system; the “Decision Maker” is the person using the DSS in order to get advice. “Dialog” is the interface between the system and the user; “Dbase management system” is the way that the system organizes and manages the dbase section of the DSS; and “Model base Management system” is the way that the system uses the data in order to provide assistance for the “decision maker”. dbase Internal data External data

Dbase management system

Model base Management System

Model Base

Document Based data

Dialog

Decision Maker

Figure 20: DSS Concept25

Besides DSS theory it is rather essential to refer also to Expert Systems theory; according to Luconi et al. (1986) an Expert System is a computer program that uses specialized symbolic reasoning to solve difficult problems well. According to the definition, Expert Systems are able to tackle a specific number of complicated problems; on the other hand a DSS is able to assist with the decision making of a more general area as long as the dbase is utilized in the appropriate manner. SUSI serves multiple objectives; thus it cannot be considered as an Expert System. 25

Sprague, R. H., et al.: Decision Support Systems: Putting Theory Into Practice, Prentice-Hall. Englewood Cliffs, N.J., 1993.

40

Theory

3.3.2

Databases

According Teich et al. (2004) there are five types of dbase structures: i.

hierarchic dbase

ii.

network dbase

iii.

relational dbase

iv.

object oriented dbase

v.

object relational dbase.

The type of dbase structure of SUSI is relational (iii). Relational dbase structure is by far the most common structure used. Data is saved in tables, connected with mathematical relationships. The connections – relationships are defined (one to one 1:1, one to many 1:n, many to many n-m). For better understanding in Figure 21 and Figure 22 an example dealing with the project administration in a company is presented. department 1

Employed m

associates n

Working-in m

project

Figure 21: Entity-Relation model of a relational dbase26 Department

Working_in

Associates

Project

Figure 22: Example data of a relational dbase27 26

Teich, P., et al.: SQL : Grundlagen und Datenbankdesign, Herdt. Nackenheim, Germany, 2004.

41

Theory

The project administration is modelled in a relational dbase as follows: Several associates belong to one department, but each associate is only employed by one department. Thus between the entities department and associate there is a 1:n-relation. Every associate can work on several projects; each project in turn can be worked on by several associates. Between the entities associate and project there is a n:m-relation. As far as the development of the dbase is concerned the theoretical background was based on the guidelines of the official manual of Microsoft Access 2000 and 2002 and other assisting books concerning the pre-mentioned software package. According to Catapult Inc. (1999) there are four basic steps that have to be made before commencing with the creation of the dbase: ƒ

Consideration of the need of the dbase

ƒ

Define the basic elements of the dbase

ƒ

Give attributes to the elements

ƒ

Define and prepare documentation concerning the elements and the relationships between them.

According to Sussman et al. (2004) the process of developing the dbase is composed of a procedure which has to repeat itself several times until the final dbase structure is ready; the components are:

27

ƒ

Analysis

ƒ

Design

ƒ

Coding

ƒ

Testing

ƒ

Documentation

ƒ

Acceptance

ƒ

Review

Teich, P., et al.: SQL : Grundlagen und Datenbankdesign, Herdt. Nackenheim, Germany, 2004.

42

Theory

Preliminary analysis

Hi-Level Design

Detailed design

Detailed design

Detailed design

Coding

Coding

Coding

Testing

Testing

Testing

Documentation

Documentation

Documentation

Acceptance

Acceptance

Acceptance Review

Review

Review

Review

Figure 23: Dbase developing procedure28

Of course the structure of the dbase builds up and the procedure starts over again from where it stopped the last time. Figure 23 depicts the procedure proposed by Sussman et al. (2004); the preliminary analysis is similar to the four basic steps proposed by Catapult Inc. (1999). “High-Level Design” refers to the first approach that the developers of dbase make towards the organization of the whole system. According this first plan the development of the dbase begins and the structure is continuously revised throughout the development.

28

Sussman, D., et al.: Beginning Access 2003 VBA, Wrox John Wiley. Indianapolis, 2004.

43

Sustainable Urban Transport System Investigation (SUSI)

4

Sustainable Urban Transport System Investigation (SUSI)

In this chapter the development of the model Sustainable Urban Transport System Investigation (SUSI) is described. It begins with the definition of the goal and scope (4.1), continues with the development of the conceptual system and the implementation of the model (4.2). After developing the conception of the decision support system (4.3), the chapter concludes with an example for a better understanding of the functions that SUSI provides (4.4).

4.1

Defintion of Goal and Scope

Intended application The goal of SUSI can be grouped into two main parts. Firstly, it offers a “pedagogic handbook” to guide decision makers that do not possess sufficient knowledge about alternative fuels (Descriptive Model). Secondly, SUSI aims to help decision makers in finding the “best” fuel according to the goals and characteristics of the decision maker’s location (Decision Support System - DSS). Motivation of SUSI Alternative fuel systems differ in environmental burden, in economics and in technical as well as socio-economic aspects. Therefore it is essential to have a complete picture about the broad effects which an alternative fuel system implies before decisions are made. Because today in many cases decision makers do not possess the required knowledge to estimate the effect of their decisions, there is a need for a tool that can support decisions makers in this process, especially in the early stage of decision making. Addressed Users of SUSI SUSI intends to be used by decision makers in public transportation. These are usually public transportation companies, municipality administrations and local politicians. The intended applications of a “pedagogic handbook” and “decisions support” system are more specified in the following paragraphs.

4.1.1

Descriptive Model

As mentioned in the Problem Analysis (chapter 1.3, page 7) many decision makers are not aware about the impact and consequences that a decision for or against an alternative fuel 44

Sustainable Urban Transport System Investigation (SUSI)

implies. To increase the decision maker’s awareness of these impacts and consequences is the first aim of SUSI. To achieve this SUSI needs to present information in a structured way and on a general level. The presented information needs to include all steps of a fuel life cycle “from cradle to the grave” or from “well to wheel” (chapter 3.1, page 28). Therefore SUSI contains information about ƒ

Buses for public transportation,

ƒ

Alternative fuels that can be used by the buses and their production methods,

ƒ

Feedstock required for the production of the alternative fuel and their production methods,

ƒ

Resources required for the production methods of the feedstock.

Since the knowledge of the decision makers in this field is incomplete the complexity of the model needs to be limited. Only general information about buses, alternative fuels, feedstock and resources and how they are related to each other shall be presented. For the users who seek for more detailed information SUSI shall present references or contact information where the user can find the required data. Furthermore most of the alternative fuel systems are not mature yet; they are still in the stage of research, first experienced have been gained only in demonstration projects. In order to put these experiences into use for other cities, which consider implementing an alternative fuel system, SUSI should provide an overview about ongoing or completed projects on alternative fuels. This includes a description of the project, the location where it takes place, participating authorities and companies and links to project publications.

4.1.2

Decision Support System

As a second main function SUSI provides a decision support system on alternative fuels for public transportation. Taking the goals of the decision maker and the characteristics of the location into account, SUSI finds the most promising well-to-wheels pathways. According to the MUD evaluation (see chapter 3.2, page 34) the factors that are relevant for decisions for or against alternative fuels are: ƒ

Environmental impact Global Regional Local 45

Sustainable Urban Transport System Investigation (SUSI)

ƒ

Long term access

ƒ

Public attitude

ƒ

Reliability

ƒ

Total economics

SUSI is able to calculate the impact of each well-to-wheels pathway on each of these factors considering the special conditions of the decision maker’s location. After that the well-towheels pathways are sorted according to the impact on the factor of the user’s choice in order to present the “best” alternative. The first version of SUSI (SUSI v1.0) is able to handle environmental, long term access and cost estimations; the structure of the model allows for future development to include more decision factors.

4.1.3

Summary of Definition of Goal and Scope

SUSI intends to provide a pedagogic handbook on alternative well-to-wheels systems and a DSS for decision makers is public transportation. The structure of SUSI has to fulfil the following requirements: ƒ

Flexible to accommodate all types of fuel pathways and bus technologies;

ƒ

Flexible to include all processes from well-to-wheel that have a considerable impact on a well-to-wheels pathway;

ƒ

Calculate emission and cost values for a well-to-wheel path and aggregate them into impact categories, respectively for total costs;

ƒ

Flexible to take into account individual data representing local conditions;

ƒ

User friendly model with reduced complexity compared to existing tools.

4.2

System Description

This section describes the structure of the model that is used to fulfil the goals explained in the goal and scope definition in the previous section (4.1). It contains the development of the main concept, the definition of data elements and explanation of the implementation process. Complementary information concerning the system can be found in Appendix 1, which contains the relationships of the basic Access tables.

46

Sustainable Urban Transport System Investigation (SUSI)

4.2.1

Main concept

As mentioned in chapter 3.1.1 (page 28), LCA is a tool for the analysis of the environmental burden of products and services at all stages of their life cycle – from the extraction of resources, through the production of materials, product parts and the product itself, and the use of the product to the management after it is discarded, either by reuse, recycling or final disposal (in effect therefore “from the cradle to the grave”) (Guinée et al., 2001). In chapter 3.1.2 (page 31) a Well-to-Wheels (WtW) analysis is described as an assessment of energy consumption and emissions of a well-to-wheels system. It covers all stages of the system including the energy feedstock recovery (wells) to the energy delivered to the wheels of the vehicle (wheels). Compared to a LCA, in a WtW analysis generally only the operation activities are included. Activities related to building infrastructures, such as manufacturing plants, filling station, roads, and equipment as well as the treatment after the end of the infrastructure’s life is not considered. Figure 24 provides an overview about the structure of the well-to-wheels pathway with all its components using the LCA framework. A well-to-wheel pathway describes the transformation of resources into a fuel and its usage in a vehicle. In a well-to-wheels pathway the resource energy is transformed or conditioned into feedstock energy which then is transformed into a fuel.

Figure 24: LCA structure of a well-to-wheels pathway

47

Sustainable Urban Transport System Investigation (SUSI)

Although the number of energy transformation or conditioning processes differs a lot from fuel path to fuel path it can be assumed that the structure of a well-to-wheels pathway in general consists of four main stages: ƒ

Resources

ƒ

Feedstock

ƒ

Fuel

ƒ

Bus

According to the LCA framework each of these four main stages consists of four life cycle steps: ƒ

Resources

ƒ

Production

ƒ

Operation/Use phase

ƒ

End of Life

System boundaries and considered flows have been chosen according to the WtW methodology (chapter 3.1.2, page 31). Therefore considered flows are only the emissions, energy use and cost of the single processes. The system boundaries line indicates that only the operation activities are integrated, the production and end-of-life use of all kinds of infrastructure and the bus are disregarded. Taking these issues into account, SUSI is based on a concept that is depicted in Figure 25.

48

Sustainable Urban Transport System Investigation (SUSI)

Note: SUSI is a tool to compare emissions and costs of well-to-wheels pathways including the processes from the Resource over its transformation into Feedstock and Fuel to the wheel of the Bus. Considered are the energy use, emissions and cost of each process in the pathway which are aggregated into total emissions and total costs for the whole pathway. The energy use, emissions and cost of the processes are not calculated in SUSI; they are considered as input data that has been calculated in WtW or LCA studies. Figure 25: SUSI Concept

The well-to-wheels pathway is split into three stages: ƒ

Feedstock path

ƒ

Fuel path

ƒ

Bus

These stages are described in more detail in the following section. Feedstock path The feedstock path includes all processes required to transform the resource energy to feedstock energy that is necessary for the fuel production. It contains the extraction of the resources, conditioning, distribution, storage, etc. and the transformation process from resource into feedstock. Each process is defined firstly, by its energy required to produce or to process 1 MJ of the feedstock, and secondly by the emissions produced in this process. Input value is therefore the energy use in the form of resources, output are emissions. Energy use and emissions of each process are added to total energy use and total emissions of the feedstock path. Cost values are not defined for each process; a cost value is defined for the whole path instead.

49

Sustainable Urban Transport System Investigation (SUSI)

Fuel Path The fuel path includes all processes required to transform the feedstock energy to fuel energy. It contains the production, conditioning, distribution, storage, etc. and the filling of the vehicle tank as the last process of the fuel path. Each process is defined again firstly by its energy required to produce or to process 1 MJ of the fuel and secondly by the emissions produced in this process. Compared to a feedstock path process a fuel path process has an additional characteristic. For each process a cost value is defined, representing all cost including operational and capital cost for producing or processing 1 MJ of the fuel. Input value for a fuel path process is therefore the energy use, this time in the form of feedstock, output value are emissions as well as costs. Furthermore it has to be defined, in which way the feedstock as energy input in the fuel path is produced. This is done by allocating a feedstock path to the fuel path process. In this way fuel path and feedstock path are aggregated into a Well-to-Tank path as a chain of processes required to transform resource energy into fuel energy. For this Well-to-Tank path, total emissions, total energy use and total costs can be calculated by adding up the values of each process of the chain.

Bus The last step of the fuel path was the filling of the fuel into the vehicle tank. Here the energy contained in the fuel is transformed into energy to power the bus. It covers therefore the Tankto-Wheel stage of Well-to-Wheel analysis. The bus as a stage in SUSI is defined by the energy required to move the bus, the emissions that are produced in this process and its operating and capital cost. Input value for the bus is therefore the energy use, this time in the form of fuel energy, output values are emissions and costs. Example: On-Site Steam reforming By means of an example Figure 26 displays how a well-to-wheel path is modelled in SUSI. A fuel cell bus requires hydrogen as fuel. The hydrogen is produced by steam reforming. This production method required two kinds of feedstock: Natural gas and electricity. The resource natural Gas needs to be conditioned, in this case purified, before it can be used in the steam reformer. The electricity is generated out of the resource coal.

50

Sustainable Urban Transport System Investigation (SUSI)

Figure 26: Example of a Well-to-Wheel path in SUSI

4.2.2

Data elements

The previous section introduced the main concept of the model providing a suitable structure for fulfilling the demanded functions, mentioned in section 4.1. In order to provide a pedagogic handbook as well as a decision support system, this structure has to be filled with data elements. This section defines the data elements which are needed in order to achieve this. The functions of SUSI were grouped into two parts: A descriptive model and a decision support system. The same is considered for the data elements as well. They can be grouped into descriptive data elements and DSS data elements. Descriptive Model The descriptive data elements contain all kinds of information necessary to teach the decision maker about alternative fuel systems, e.g. characteristics of a resource, feedstock, fuel and a bus, but also information about participating companies in demonstration projects, project cities, etc. Decision Support System The descriptive model and the DSS are based on the same structure, using the same data elements. The DSS, however, requires additional information that is not used in the descriptive model. The descriptive model only provides qualitative data, e.g. which processes belong to a fuel path and which feedstock are used in this fuel path. It does not provide any 51

Sustainable Urban Transport System Investigation (SUSI)

quantitative information, e.g. how much emissions are produced and how much of the feedstock is needed, because these values highly depend on local characteristics and therefore no generally meaningful values could be presented in the descriptive model. Energy use, emissions data and other values that account for the calculations of the decision factors are the DSS data elements. These additional data elements are only used in the DSS. To guarantee that the calculations are based on the individual data of the decision maker, each decision maker can use standard pre-defined data sets, but also create his own profile in SUSI and edit, import end export his data for each session he wants to use SUSI.

4.2.3

Implementation

This section of the thesis is dedicated to explain the way how the theory concerning the DSS and the dbase (chapter 3.3) was used in order to develop SUSI. Although the theoretical background concerning DSS and dbases differs, the developing of a system that encompasses both concepts commands that the design and development is done simultaneously and theory from both notions is used. Before commencing with the designing of the system it was essential to define the roles of the stakeholders of the DSS; approver and administrator was TFK (Dr. Magnus Blinge), developer was Chalmers University (S. Behrends and P.Georgousis). Operator and User of output are public transport operators, municipalities and local politicians; these roles are not assigned to specific persons, but still the concepts had to be defined in order to proceed with the design of the system. The roles of each group are better explained in Figure 27.

Figure 27: DSS Stakeholders

In general, the process followed during the development phase was the one proposed by Sussman et al. (2004) (Figure 28). The first step was for the “approver & administrator” and the “developer” to define the system and its capabilities. This was done according to the guidelines of Catapult Inc. (1999). Preliminary analysis and hi-level design followed.

52

Sustainable Urban Transport System Investigation (SUSI)

Then, each section of the system was first designed, developed in Access 2002 and then tested; for the testing phase sample data was inputted in the system and several trials were made in order to proof the functionality of the system. Afterwards, the documentation of the coding procedure followed.

Figure 28: Dbase developing procedure29

After each segment was created and intergraded in the system it had to be tested again and approved by the “Approver and Administrator”. This was done mostly in meetings and the “developer” implemented any proposed changes but starting again from the “Detailed design” step. The outcome of this evolving procedure was SUSI.

Figure 29: Sprague DSS concept vs. SUSI concept

29

Sussman, D., et al.: Beginning Access 2003 VBA, Wrox John Wiley. Indianapolis, 2004.

53

Sustainable Urban Transport System Investigation (SUSI)

As described by Sprague et al. (1993) SUSI has the following structure (Figure 29, on the left side the model by Sprague is presented and on the right side the outcome of SUSI); a) Starting from the “Decision Maker” which in the case of SUSI is the “User”; according to the aim of SUSI the user of the output (decision maker) should be able to have a hand on ability with the system. b) Since SUSI is developed in Access 2002, the “Forms” are the “dialog” component. c) The “filters” constitute the way that SUSI arranges the dbase; the dbase has three main data sources: i) internal data: data stored already in the dbase; ii) external data: data accessed from external sources such as links to the web; iii) document based data: data stored in documents. d) The “Delimitation Process and filtering of Results” constitute the “Model Base Management System”; the difference is that the “Model Base” of SUSI is the internal dbase, decision support provided by SUSI is based on the internal data.

4.3

Decision Support System

The DSS aims to find the most suitable alternative well-to-wheels pathway for a decision maker taking his/her goals and the characteristics of the location into account. As discussed in the chapter 3.1.1 (page 28) support in decision making is one application of an LCA. Therefore the DSS in SUSI is aligned with the LCA framework (Inventory analysis and impact assessment). This section describes in detail the functionalities of the DSS in SUSI. First, it is described how the emissions and costs are calculated for the whole pathway (Inventory Analysis). After that, the inventory is aggregated into the impact categories representing the set of goals of the decision makers (Impact Assessment). Finally, when the impacts for all pathways are available SUSI delimitates the pathways that are not feasible for the user according to the characteristics of his location (Delimitation process). These steps are described below in more detail.

4.3.1

Inventory Analysis

Inventory analysis includes the development of a system model according to the requirements of the goal and scope definition. The result is a mass and energy balance of environmentally relevant flows, which include use of scarce resources and emissions of substances considered harmful as well as costs.

54

Sustainable Urban Transport System Investigation (SUSI)

In this section the considered data elements, the structure of the flow model feedstock path – fuel path – bus and the calculations of the total values for the whole system are presented. For better understanding a calculation example is included. Considered Data elements In the theory review in chapter 3.2 (page 34) the decision factors determining the decision making on alternative fuel system were discussed. Noise as an environmental impact, reliability and the public attitude are disregarded as decision factors in SUSI v1.0. The considered decision factors and data elements are: ƒ

Global warming (GWP)

ƒ

Acidification (AP)

ƒ

Eutrophication (EP)

ƒ

Ozone at ground level (POCP)

ƒ

Human health (HTP)

ƒ

Long term access (Consumption of non-renewable resources)

ƒ

Total economics (WTW cost)

The data elements accounting for these decision factors are: ƒ

Carbon dioxide (CO2)

ƒ

Methane (CH4)

ƒ

Nitrous oxide (N2O)

ƒ

Nitrogen oxide (NOx)

ƒ

Sulphur oxide (SO2)

ƒ

Volatile organic compounds (VOC)

ƒ

Carbon oxide (CO)

ƒ

Particles (PM)

ƒ

Energy use

ƒ

Cost

In SUSI a well-to-tank path consists of a chain of fuel path- and feedstock path processes. Each process is defined by these data elements. The WtT values are calculated by summing up these data elements of each process of a WtT chain. The calculation concept is explained in the following section. Functional units for the analysis of the fuel path are: ƒ

Energy use:

MJ ex MJ F

MJ expended to process/produce 1MJ of the fuel/feedstock 55

Sustainable Urban Transport System Investigation (SUSI)

ƒ

Emissions:

g MJ F

grams of the substance emitted to process/produce 1MJ of the fuel/feedstock

The Fuel path represents the transformation of the resource over feedstock to fuel. Therefore the calculation has to include the feedstock path processes and fuel path processes to include the whole impact of the path. Feedstock path The Feedstock path emissions for producing 1 MJ of the feedstock are calculated by summing up the emissions values of each process in the chain: FeedstockPathEmissions =

Pr ocess

∑

⎡ ⎤ g ⎢ ⎥ ⎣ MJ Feedstock ⎦

g MJ Feedstock

In the example introduced in Figure 26 (page 51) there are two feedstocks needed for the fuel path process steam reforming: Electricity and Natural Gas. Table 4 displays the calculation of the total fuel path emissions (the data contained in the table is no “real” data, it was chosen without any meaning just for demonstration purposes). For the feedstock path “Electricity Grid-Mix Germany” only one process is considered: Electricity Generation (Grid). This process needs 2,2 MJ of the resource coal to produce 1 MJ of the feedstock electricity. In this process emissions are produced, as indicated in the table. 1 MJ of electricity from the German grid mix costs 0,065 €. The feedstock path for the natural gas contains two processes. In this case natural gas is both, resource and feedstock. No energy transformation takes place. However, the resource is usually not usable for fuel production without any pre-treatment and without distribution. These processes are included in the feedstock path. For extracting and processing 1 MJ of Natural Gas (NG) 1,3 MJ of NG are required. Then the NG is transported to the steam reformer by pipeline. This process consumes 0,1 MJ per MJ transported NG. The total resource energy demand of the process is therefore 1,4 MJ. Table 4: Example feedstock path calculations Feedstock Path processes

Grid-Mix Germany Electricity generation (Grid) Total NG Production - Distribution NG Extraction & Processing NG Transport, piped 7000km Total

56

Emissions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] 10,0 10,0

8,0 8,0

1,0 1,0

3,0 3,0

8,0 8,0

7,0 7,0

3,0 3,0

2,0 2,0

1,0 1,0 2,0

2,0 2,0 4,0

1,0 3,0 4,0

1,0 1,0 2,0

2,0 4,0 6,0

4,0 2,0 6,0

1,0 1,0 2,0

2,0 1,0 3,0

Feedstock Cost Market price [€/MJ]

Resource Energy Type [MJr/MJfs]

0,065

2,2 2,2

Coal

0,035

1,3 Natural Gas 0,1 Natural Gas 1,4

Sustainable Urban Transport System Investigation (SUSI)

Fuel path The total emissions of producing 1 MJ fuel of a fuel path consist of two parts. Besides the direct emissions that are produced in the fuel path process, the emissions of the feedstock production that is used for the process have to be considered as well. Therefore the total emissions of the fuel path are:

FuelPathEmissions =

Pr ocess

∑

⎛ g ⎞ MJ Feedstock ⎜⎜ + × FeedstockPathEmissions ⎟⎟ MJ Fuel ⎝ MJ Fuel ⎠

⎡ g ⎤ ⎢ ⎥ ⎣ MJ Fuel ⎦

Each fuel path process produces direct emissions, represented in the first part of the equation ⎛ g ⎞. ⎜⎜ ⎟⎟ ⎝ MJ Fuel ⎠

Table 5: Example Fuel path calculations - direct emissions Fuel Path processes

Steam Reforming (on-site) Hydrogen Purification Hydrogen Compression Hydrogen Storage - 350 bar Hydrogen Dispensing Sum(Fuel path processes)

Emissions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] 3,0 1,0 2,0 3,0 1,0 2,0 1,0 1,0 0,0 0,0 0,0 0,0 3,0

0,0 0,0 0,0 0,0 1,0

0,0 0,0 0,0 0,0 2,0

0,0 0,0 0,0 0,0 3,0

0,0 0,0 0,0 0,0 1,0

0,0 0,0 0,0 0,0 2,0

0,0 0,0 0,0 0,0 1,0

0,0 0,0 0,0 0,0 1,0

Cost [€/MJ] 0,270 0,020 0,040 0,100 0,010 0,440

Feedstock Energy Type [MJfs/MJf] 0,3 Electricity 1,7 Natural Gas 0,2 Electricity 0,1 Electricity 0,3 Electricity 0,1 Electricity 2,7

Table 5 presents the hydrogen production by steam reforming as example of a fuel path. It consists of five processes: Steam reforming, purification, compression, storage and dispensing. Each process needs feedstock energy. Steam reforming requires with electricity and natural gas two feedstocks, the other processes require electricity. Only the steam reforming produces direct emissions because of the combustion of the natural gas. The other processes have no direct emissions. The cost represents the capital and operating cost for producing 1 MJ of hydrogen. The second part of the equation calculates the emissions from the feedstock that is used by process. A fuel path process needs a certain amount of feedstock energy in order to produce/process 1 MJ of the fuel ⎛⎜ MJ Feedstock ⎞⎟ . By multiplying this with the feedstock path values ⎜ MJ ⎟ Fuel ⎝ ⎠

(see Table 4) the indirect emissions of the fuel path process are calculated. An example is presented in Table 6:

57

Sustainable Urban Transport System Investigation (SUSI)

Table 6: Example Fuel Path Calculations - Indirect emissions from Feedstock path Fue l Pa th proce sse s

Steam Reforming (on-site) Hydrogen Purification Hydrogen Compression Hydrogen Storage - 350 bar Hydrogen Dispensing Sum (Fue l pa th proce sse s)

Em issions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] 3,0 2,4 0,3 0,9 2,4 2,1 0,9 0,6 6,8 6,8 3,4 10,2 10,2 3,4 5,1 3,4 2,0 1,6 0,2 0,6 1,6 1,4 0,6 0,4 1,0 0,8 0,1 0,3 0,8 0,7 0,3 0,2 3,0 2,4 0,3 0,9 2,4 2,1 0,9 0,6 1,0 0,8 0,1 0,3 0,8 0,7 0,3 0,2 13,4 14,8 7,8 6,4 18,2 17,2 6,4 7,1

Cost [€/MJ] 0,020 0,060 0,013 0,007 0,020 0,007 0,125

Fe e dstock Energy Type [MJr/MJfs] 0,3 Electricity 1,7 Natural Gas 0,2 Electricity 0,1 Electricity 0,3 Electricity 0,1 Electricity 2,7

As an example the calculation of the indirect fuel path CO2 emissions from the Steam reforming process for Natural gas is calculated in the following equation. (The taken values are marked in red-coloured script in the tables.)

Indirect _ FuelPathEmissions _ CO 2 =

MJ Feedstock × FeedstockPath _ CO 2 = 1,7 × 2 = 3,4 MJ Fuel

Costs generally are calculated in the same way, but are only considered for the fuel path processes. Since the feedstock path is mostly not in the responsibility of the cities, bus operators, etc, cost for the feedstock path processes are not relevant. The final cost of a feedstock path is in most cases the market price, like for grid mix electricity or natural gas from a certain location. Summing up the total emissions/cost of each fuel path process, results in the total emissions/cost of the fuel path (Well-to-Tank path). For the used example these are presented in Table 7: Table 7: Example Fuel Path Calculations - Total Well-to-Tank Fue l Pa th proce sse s

Steam Reforming (on-site) Hydrogen Purification Hydrogen Compression Hydrogen Storage - 350 bar Hydrogen Dispensing Sum W e ll-to-Ta nk

Em issions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] [g/MJ] 9,4 10,2 9,1 7,3 13,6 14,3 5,3 6,7 2,0 1,6 0,2 0,6 1,6 1,4 0,6 0,4 1,0 0,8 0,1 0,3 0,8 0,7 0,3 0,2 3,0 2,4 0,3 0,9 2,4 2,1 0,9 0,6 1,0 0,8 0,1 0,3 0,8 0,7 0,3 0,2 16,4 15,8 9,8 9,4 19,2 19,2 7,4 8,1

Cost [€/MJ] 0,349 0,033 0,047 0,120 0,017 0,565

Well-to-Wheels integration Every data element is calculated in the way described before for each WtT path. The TtW path consists only of one “process”: the bus. For the bus the data elements are direct available; no calculations are needed.

⎡ g ⎤ ⎡ g ⎤ ⎡ g ⎤ WtT ⎢ ⎥ and TtW ⎢ ⎥ are integrated into WtW ⎢ ⎥ by using the following equation: ⎣ km ⎦ ⎣ km ⎦ ⎣ MJ F ⎦

58

Sustainable Urban Transport System Investigation (SUSI)

⎡ g ⎤ ⎡ MJ F ⎤ ⎡ g ⎤ ⎡ g ⎤ WtW _ Emissions⎢ ⎥ = WtT _ Emissions⎢ + Bus _ Emissions⎢ ⎥ ⎥ × FuelConsumption⎢ ⎥ ⎣ km ⎦ ⎣ km ⎦ ⎣ km ⎦ ⎣ MJ F ⎦

⎡ € ⎤ ⎡ MJ F ⎤ ⎡ € ⎤ ⎡ € ⎤ + Bus _ Cost ⎢ ⎥ WtW _ Cost ⎢ ⎥ = WtT _ Cost ⎢ ⎥ × FuelConsumption⎢ ⎥ ⎣ km ⎦ ⎣ km ⎦ ⎣ km ⎦ ⎣ MJ F ⎦ Table 8 shows as example for a TtW the FC bus. The FC bus is emissions-free. The cost are 0,85 €/km and it consumes 2,7 MJ hydrogen per km. Table 8: Example Tank-to-Wheels Emissions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] 0,0 0,0 0,0 0,0 0,0 0,0 0,0 0,0

Bus

FC Bus

Cost [€/km] 0,850

Fue l Energy Type [MJf/km] 2,7 Hydrogen

Using the equations shown above the total WtW emissions and costs for a FC Bus using H2 produced by steam reforming are: Table 9: Example total Well-to-Wheels emissions Tota l W e ll-to-W hee ls

FC Bus, H2, Ste am Re f.

Em issions CO2 CH4 N2O CO Nox SO2 NMVOC PM [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] [g/km] 44,3 42,7 26,5 25,4 51,8 51,8 20,0 21,9

WtW _ CO2 = WtT _ CO2 × FuelConsumption + Bus _ CO2 = 16,4

Cost [€/km] 2,374

MJ H 2 g g g × 2,7 + 0,0 = 44,3 MJ H 2 km km km

Now the data elements are available from well to wheels. In order to evaluate the well-towheels path the data elements have to be aggregated into impact categories which represent the decision factors. How this is done in SUSI is described in the next section.

4.3.2

Impact Assessment

In the impact assessment the single data elements are aggregated into impact categories according to their influence they have on them. It aims to describe or to indicate the impact of the environmental loads quantified in the inventory analysis. The data elements which account for the impact categories were discussed in chapter 3.2. This section presents the mathematic model used to aggregate the data elements into the impact categories. Many different models exist describing the impact of the environmental loads in a different way. The models used in SUSI are based on CML 2002 (Baumann et al., 2004). Only the main data elements are considered. However, there are many more substances having an impact, but since they don’t play an important role in transport emissions, they are disregarded in SUSI.

59

Sustainable Urban Transport System Investigation (SUSI)

ƒ

Climate Change

The climate change or global warming is caused by the emissions CO2, CH4 and N2O. These emissions contribute to a different intensity to the global warming. Their effect is also depending on the time horizon. According to (Lindfors, 1998) the global warming potential on a 100-year basis shall be used. Therefore, in SUSI the relative to CO2 potentials are: GWP100 = 1 ⋅ CO2 + 21 ⋅ CH 4 + 310 ⋅ N 2 O ƒ

[kg ⋅ CO

30

2 equiv

]

Acidification

The acidification potential is expressed relative to the SO2. It is calculated by: AP = 1 ⋅ SO2 + 0,7 ⋅ NOx ƒ

[kg ⋅ SO

30

2 equiv

]

Eutrophication

The eutrophication potential is expressed relative to the PO (phosphorus). EP = 0,13 ⋅ NOx ƒ

[g ⋅ PO

3− 4equiv

30

]

Ozone at ground level

The photochemical ozone creation potential is expressed relative to ethylene

POCP = 0,027 ⋅ CO + 0,006 ⋅ CH 4 + 0,364 ⋅ NMVOC ƒ

31

[g ⋅ ethylene ] equiv

Human health

The Human toxicity potential (HTP):

HTP = 0,096 ⋅ SO2 + 0,082 ⋅ PM + 0,05848 ⋅ NMVOC ƒ

31

[g ⋅ 1,4 − dichlorbenzene ] equiv

Long term access

The long term access refers to the depletion of non-renewable resources. In SUSI a fuel is considered to offer a long term access if its resources are renewable. In this sense long term access is referred by “Consumption of non-renewable resources” in SUSI v1.0 which calculates the consumption of non-renewable resources. ƒ

Total economics

In SUSI v1.0 the economic impact is considered in a way which represents the costs for the fuel, the operation of the bus and the operation of the required infrastructure. Costs or benefits for the society or other impacts are not included. The costs are calculated by the equation: WtW _ Cost = WtT _ Cost × FuelConsumption + Bus _ Cost 30

Baumann, H., et al.: The Hitch Hiker's Guide to LCA: An orientation in life cycle assessment methodology and application, Studentlitteratur. Lund, 2004. 31 Faltenbacher, M: Personal communication March 2005

60

Sustainable Urban Transport System Investigation (SUSI)

This figure was already calculated in the inventory analysis (see 4.3.1). Since it is the only considered cost figure there is no need for an aggregation with other data elements.

4.3.3

Delimitation process

The delimitation process is the heart of the DSS tool. In Figure 30 the delimitation process is depicted. The outcome of the impact assessment is a long list of all well-to-wheels pathways contained in the database with their calculated impacts. However, some well-to-wheels pathways are not suitable for the decision maker for various reasons, e.g. the decision maker has no access to a specific feedstock supply. To delimitate these is the purpose of the delimitation process of SUSI. Before doing this, the decision maker has to specify to which feedstock he has access to and by which paths these feedstocks are supplied in the user profile settings (view Appendix 2: SUSI Manual). Then, when the user starts the delimitation process, SUSI chooses only those paths that correspond to the user profile settings and presents them in a list that contains only those pathways that use the in the user profile settings named feedstock paths. Then the user can sort the remaining pathways according to several decision factors and find the “best” fuel.

Figure 30: Concept of the Delimitation process

4.4

Results

This section provides the results of SUSI by presenting a simple example in order to get a better understanding about the functions of the model. After introducing the sample data that is used in this example, it is shown on the basis of three users how SUSI can support decision makers in public transportation in reaching their goals.

4.4.1

Sample Data

In order to pinpoint the functionality of SUSI the data chosen for this example is kept on a simple level. However, it is of importance to highlight that the results presented here are not based on accurate data, since data filling is not subject of this thesis. Neither the fuel paths nor feedstock paths may be exhaustive, as well as the processes may contain incomplete values. On the other hand, the figures are based on Baumann et al.; therefore they represent the main 61

Sustainable Urban Transport System Investigation (SUSI)

drivers of each fuel- and feedstock path. Thus, the results presented in this example may provide indicators about the performance of the included well-to-wheel pathways. The following section presents the sample data, which was used in this example. Fuel paths In this example two hydrogen fuel paths with the following feedstock paths are considered: ƒ

Hydrogen by On-Site Electrolysis o with Electricity from Grid-Mix o with Electricity from Biomass o with Electricity from Wind

ƒ

Hydrogen by On-Site Steam reforming o with Natural Gas from Russia and Grid Mix Electricity

Feedstock Paths The electricity grid-mixes differ in their composition of resources from country to country. This example includes three different grid-mixes: EU average, Sweden and Germany. The resource composition is presented in Table 10 and Figure 31, including also the electricity production from biomass and wind, respectively (Baumann et al., 2004). Table 10: Electricity Feedstock Paths - Resources Resource input [%] Coal, EU Oil, M.East NG, Russia Nuclear Electricity Production - Grid Mix - EU Average 27 10 15 35 Electricity Production - Grid Mix - Sweden 50 Electricity Production - Grid Mix - Germany 56 11 30 Electricity Production - Biomass Electricity Production - Wind

Hydro 13 50 3

Biomass

100 100

120

100

%

80 Coal, EU Oil, M.East NG, Russia Nuclear Hydro Biomass Wind

60

40

20

0 Electricity Production Grid Mix - EU Average

Electricity Production Grid Mix - Sweden

Electricity Production Grid Mix - Germany

Electricity Production Biomass

Electricity Production Wind

Figure 31: Electricity Feedstock Paths – Resources

62

Wind

Sum 100 100 100 100 100

Sustainable Urban Transport System Investigation (SUSI)

User Profile Data In this example, three different decision makers use SUSI in order to find their best alternative fuel pathway: the Göteborg Municipality, the Hamburg public transport operator and the Commission of the EU. The following feedstock pathways are available in the locations: ƒ

Göteborg o Electricity Production – Grid-Mix Sweden o Electricity Production – Biomass o Natural Gas – Russia

ƒ

Hamburg o Electricity Production – Grid-Mix Germany o Electricity Production – Wind o Natural Gas – Russia

ƒ

EU average o Electricity Production – Grid-Mix EU-Average o Electricity Production – Biomass o Electricity Production – Wind o Natural Gas – Russia

Every location has access to the grid-mix of its country as well as to natural gas from Russia. Furthermore, due to special local conditions, Göteborg has also access to electricity produced from biomass (waste wood), a waste product of the forestry industry, whereas Hamburg has access to electricity produced by offshore windmills in the North Sea. The EU commission uses the EU average conditions. It is assumed in this example that for EU average every feedstock path as available. The goals of introducing an alternative fuel bus system differ among the decision makers. The Göteborg Municipality seeks to achieve a sustainable transport system and switch its fuel supply totally on fuel produced from renewable sources. The Hamburg bus operator intends to minimize the cost, while the EU commission seeks to minimize the global warming impact. Their decision factors in SUSI are therefore: ƒ

EU Commission

Æ

Minimizing global warming potential (GWP)

ƒ

Hamburg Bus Operator

Æ

Minimizing cost (WtW cost)

ƒ

Göteborg Municipality

Æ

Minimizing the consumption of non-renewable resources

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Sustainable Urban Transport System Investigation (SUSI)

4.4.2

Application of SUSI

EU-Commission Running the DSS procedure using the settings of the EU Commission delivers the results shown in Figure 32. This window presents the global warming potential GWP, eutrophication potential EP, acidification potential AP, human toxicity potential HTP, the consumption of non-renewable resources and the WtW costs of each WtW pathway. The WtW pathway is specified by the fuel type, fuel path name and bus name. Producing hydrogen by On-site Electrolysis – Wind Power is the most promising well-towheels path in order to minimize the global warming impact under EU average conditions (22 g CO2 equiv/km). It is followed by On-site Electrolysis – biomass (185) and On-site Steam Reforming (866). The by far biggest global impact would be caused by On-site Electrolysis – Grid-Mix (2.588).

Figure 32: SUSI Well-to-Wheels Results (EU Average Conditions)

Göteborg Municipality The DSS results using the Göteborg settings are shown in Figure 33. The well-to-wheels paths are sorted by Consumption of non-renewable Resources. The WtW path On-site electrolysis – Wind power is not presented here, because in Göteborg the required feedstock path Electricity production from Wind is not available. The most promising WtW path in order to minimize the consumption of non-renewable resources is On-site electrolysis – Biomass. Since the feedstock is based completely on the renewable resource wood, no nonrenewable resources are consumed. On-site steam reforming – NG Russia is the second best option (0,8 MJ/km) followed by On-site electrolysis – Grid-Mix (2,2 MJ/km).

64

Sustainable Urban Transport System Investigation (SUSI)

Figure 33: SUSI Well-to-Wheels Results (Göteborg Conditions)

The importance of using local conditions instead of average figures is highlighted by the fact, that under Göteborg conditions the WtW path On-site Electrolysis – Grid-Mix has the lowest Global Warming Impact (12 g CO2 equiv/km). Using the European settings On-site Electrolysis – Grid-Mix is by far the WtW path with the highest Global Warming Impact (2.588), and would therefore lead to wrong decision of the Göteborg municipality. Hamburg Bus Operator The DSS results using the local conditions of Hamburg are depicted in Figure 34. The wellto-wheels paths are sorted by WtW cost. The WtW path On-site electrolysis – Biomass is not presented here, because in Hamburg the feedstock path electricity production from Biomass is not available. The most promising WtW path in order to minimize the consumption of nonrenewable resources is On-site Steam Reforming – NG Russia (1,44 €/km). On-site Electrolysis – Grid-Mix is the second best option (1,75 €/km) followed by On-site Electrolysis – Wind Power (1,83 €/km).

Figure 34: SUSI Well-to-Wheels Results (Hamburg Conditions)

65

Sustainable Urban Transport System Investigation (SUSI)

Summary This example shows that WtW pathways differ in environmental and economical performance. Thus it depends on the goals of the decision maker which WtW pathway is suitable to meet the decision maker’s needs. Furthermore this example highlights the influence of local characteristics on the performance of the WtW paths and that they have to be considered in the decision making process to avoid misleading decisions. With the help of SUSI it is possible for the decision maker to evaluate the differing performance of well-to-wheel pathways while taking local conditions into account.

66

Conclusions and Recommendations

5

Conclusions and Recommendations

General Conclusions SUSI, as set by the aims of the thesis, provides a well defined structure for the “pedagogic handbook" for the usage of alternative fuels and the structure for the DSS model concerning alternative fuel schemes. The dbase structure of SUSI is capable of handling information concerning all alternative fuels and technologies. Furthermore, SUSI is a DSS tool which is able to compare alternative fuel production and operation schemes according to the characteristics of the user. The structure of the DSS model is open for further improvements and additional features can be added in order to enhance the capabilities of the system. Decision makers, such as politicians and public bus operators, lack a system that would help them in the first step of the learning process concerning alternative fuels and their usage. Likewise, the DSS model that SUSI proposes can help decision makers in their first approach concerning a decision process; but also make them understand the logic behind the complexity of the decision that they have to make. SUSI v1.0 does not require any expertise in order to be used making it easy to use and in a way fun to play with. Summarizing, SUSI is not an LCA tool; it is a well-to-wheel comparison model. Although the system boundaries can be extended far more than the boundaries of SUSI v1.0, further development of SUSI should concentrate in improving its current capabilities. A basic characteristic of SUSI v1.0 is that it is highly dependent on data; so, all the results coming from the DSS model depend on the quality of data that the user has inputted. As explained in the manual (Appendix 2: SUSI Manual), SUSI v1.0 can assist the user in order to find mistakes that are based on a logical background, but not data input mistakes concerning emission or cost values. Recommendations During the process of developing SUSI a lot of ideas came up in order to make the system more complete, user friendly and accurate. Developing such a system is an ongoing process and ideas never stop coming; so it was decided to make several recommendation concerning future development: ƒ

The user should be able to create his/her own impact categories; since not all impact categories (decision factors) are included in SUSI, the user should be able to create it and define its parameters. An example would be to add decision factor "reliability";

67

Conclusions and Recommendations

reliability as a term is very vague and every organisation uses its own definition, so the user can define what "reliability" is and SUSI will use it as an impact category. ƒ

Change calculation methods for existing impact categories (decision factors); as explained before the user should also be able to change the existing impact categories, for example in order to calculate the Global Warming Potential the user should be able to define his own calculation method. Another possibility would be for SUSI to make available for the user a set of calculation methods from which he/she could choose from.

ƒ

SUSI v1.0 classifies the well-to-wheels paths according to impact categories but does not provide an aggregated one-dimensional index for making comparisons; an option would be for the user to define the weight of importance of each factor and then SUSI would automatically calculate the index.

ƒ

Fuel consumption estimation is an other option that should be considered; SUSI v1.0 estimates all emissions and costs per km driven, but what is the correct fuel consumption / km driven ratio? An option could be to introduce topographic, climate, traffic characteristics and define their relationship to the bus technology so a more accurate consumption estimation could be provided.

ƒ

Furthermore SUSI could provide a better way to calculate costs, investment costs, operating (variable and fixed costs) as well as depreciation of equipment.

ƒ

In order to provide a broader view concerning economical consequences of implementing an alternative fuel scheme, the job creation potential could be also calculated in terms of human working hours.

ƒ

Finally, presenting results and reporting should be enhanced, but this should be done in accordance with the user needs. The best option should be for the user to be able to create the reporting procedure that is best for him/her.

68

References

References Conference Fuel Cells - Commercial possibilities and visions for future applications, Chalmers University of Technology, Göteborg, Sweden, 2004/05/26-27.

Conference 2nd International Fuel Cell Bus Workshop, Porto, 2004/11/18-20.

Conference First Experiences of European Fuel Cell Bus Demonstration Projects, London, 2004/06/14-15.

Alter, S.: A Taxonomy of Decision Support Systems. Sloan Management Review, 1977, 19(1).

Baumann, H., et al.: The Hitch Hiker's Guide to LCA: An orientation in life cycle assessment methodology and application, Studentlitteratur. Lund, 2004.

Blinge, M.: ELM: Environmental assessment of fuel supply systems for vehicle fleets, Chalmers University of Technology. Göteborg, 1998.

Catapult Inc.: Microsoft Access 2000 step by step, Microsoft Press. Redmond, Wash., 1999.

European Commission - Directorate-General for Energy and Transport: Green paper: Towards a European strategy for the security of energy supply, Office for Official Publications of the European Communities. Luxemburg, 2001a.

European Commission - Directorate-General for Energy and Transport: White paper: European transport policy for 2010: Time to decide, Office for Official Publications of the European Communities. Luxemburg, 2001b.

European Commission - Directorate-General for Energy and Transport: CUTE, Clean Urban Transport for Europe - A fuel cell bus project in 9 European cities, European Commission. Directorate-General for Energy and Transport. Brussels, 2002a. 69

References

European Commission - Directorate-General for Energy and Transport: Energy : Let us overcome our dependence, Office for official publications. Luxemburg, 2002b.

European Commission - Directorate-General for Energy and Transport: European Energy and Transport in Figures, Office for Official Publications of the European Communities. Luxemburg, 2003a.

European Commission - Directorate-General for Energy and Transport: European energy and transport trends to 2030, Office for Official Publications of the European Communities. Luxemburg, 2003b.

European Commission - Directorate-General for Energy and Transport: Hydrogen Energy and fuel cells: A vision of our future, Office for Official Publications of the European Communities. Luxemburg, 2003c.

European Commission - Directorate-General for Energy and Transport: Energy & Transport: Report 2000-2004, Office for Official Publications of the European Communities. Luxemburg, 2004.

European Commission - Directorate-General for Joint Research Centre: Potential for Hydrogen as a Fuel for Transport in the Long Term (2020 - 2030), Office for Official Publications of the European Communities. Luxemburg, 2004.

European Commission - Directorate-General for Joint Research Centre, et al.: Well-to-wheels analysis of future automotive fuels and powertrains in the European context, Office for Official Publications of the European Communities. Luxemburg, 2003.

European Commission - Directorate-General for Research: World energy, technology and climate policy outlook, Office for Official Publications of the European Communities. Luxemburg, 2003.

Faltenbacher, M., et al. Conference Internationaler Deutscher Wasserstoff Energietag 2004, Essen, 2004-02-11. 70

References

Faltenbacher, M., et al.: CUTE - Clean Urban Transport for Europe - Hydrogen supply infrastructure and fuel cell technology. Ulm, 2004b.

Geitmann, S.: Wasserstoff & Brennstoffzellen : die Technik von morgen!, Hydrogeit Verlag. Kremmen, 2004.

General Motors Corporation: GM well-to-wheel analysis of energy use and greenhouse gas emissions of advanced fuel/vehicle systems - a European study, L-B-Systemtechnik GmbH. Ottobrunn, 2002.

General Motors Corporation, et al.: Well-to-Wheel Energy Use and Greenhouse Gas Emissions of Advanced Fuel/Vehicle Systems – North American Analysis –, 2001.

Guinée, J. B., et al.: Life Cycle Assessment - An Operational Guide to the ISO Standards, Ministry of Housing, Spatial Planning and the Environment (VROM) Centre of Environmental Science - Leiden University (CML). Leiden, 2001.

Hekkert, M. P., et al.: Natural gas as an alternative to crude oil in automotive fuel chains: Well-to-wheel analysis and transition strategy development. Energy Policy, 2003, 33, 579594.

Hogue, J. T.: A Framework for the Examination of the Management Involvement in Decision Support Systems. Journal of Management Information Systems, 1987, 4(1), 96-110.

h-tec. PEM fuel cell. www.h-tec.com/education/eng (2005-02-01)

Institut für Kunststoffprüfung und Kunststoffkunde: GaBi 4 manual: Get ready for tomorrow, Institut für Kunststoffprüfung und Kunststoffkunde, Universität Stuttgart. Stuttgart, 2003.

Jolma, A. Conference International Congress on Modelling and Simulation, Newcastle, Australia.

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References

Karlström, M.: Environmental Technology of Introducing Fuel Cell City Buses - A case Study of Fuel Cell Buses in Göteborg, Department of Environmental Systems Analysis, Chalmers University of Technology. Göteborg, Sweden, 2002.

Kruse, B., et al.: Hydrogen - Stats og muligheter, Bellona. Oslo, 2002.

Lindfors, L.-G.: A manual for the calculation of ecoprofiles intended for third party certified environmental product performance declarations, Swedish Environmental Research Institute. Stockholm, 1998.

Luconi, F. L., et al.: Expert Systems: The Next Challenge for Managers. Sloan Management Review, 1986, 3-14.

McClaine, A. W., et al.: Chemical Hydride Slurry for Hydrogen Production and Storage. DOE Hydrogen Program, 2004, 205-209.

Ottosson, M.: ECTOS Model Guide, TFK Transport Research Institute. Göteborg, 2004.

Power, D. J.: Decision Support Systems, Concepts and Resources for Managers, Greenwood Publishing Group Inc. USA, 2002.

Sabater, I. Conference First Experiences of European Fuel Cell Bus Demonstration Projects, London, 2004/06/15.

Schindler, J. Conference European Hydrogen Energy Conference, Grenoble, France, 2003/09/03.

Sprague, R. H., et al.: Decision Support Systems: Putting Theory Into Practice, Prentice-Hall. Englewood Cliffs, N.J., 1993.

Sussman, D., et al.: Beginning Access 2003 VBA, Wrox John Wiley. Indianapolis, 2004.

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References

Teich, P., et al.: SQL : Grundlagen und Datenbankdesign, Herdt. Nackenheim, Germany, 2004.

TFK Transport Research Institute: Environmental Handbook for Transport Purchasing, TFK Transport Research Institute. Stockholm, 1998.

Wang, M.: Fuel choices for fuel cell vehicles: well-to-wheels energy and emission impacts. Journal of Power Sources, 2002, 112, 307-321.

Wang, M. Q.: Development and Use of GREET 1.6 Fuel-Cycle Model for Transportation Fuels and Vehicle Technologies, Center for Transportation Research, Energy Systems Division, Argonne National Laboratory. Argonne, 2001.

73

Appendix 1: Relationships of basic Access tables

Appendix 1: Relationships of basic Access tables

Relationships Fuel

Fuel_Data Fuel_ID Fuel_Type General Characteris FuelPath_Data Fuel_Path_ID Fuel Path name Fuel type

FuelPath_FuelPathProcess Fuel Path name Fuel Path Process name LocalForUser

FuelPathProcess_Data Fuel_Path_Process_ID Fuel Path Process name Description Logo

FuelPathProcess_Feedstock Fuel Path Process name Feedstock name Energy consumed

Feedstock_Data Feedstock_ID Feedstock type Logo Description FeedstockPath_Data ID Feedstock Path name Feedstock type Description

Resource_Data Resource_ID Resource name Renewable

FeedstockPath_FeedstockPathProce Feedstock Path name Feedstock Path Process name LocalForUser

FeedstockPathProcess_Data ID Feedstock Path Process name Description

FeedstockPathProcess_Resource Feedstock Path Process Name Resource name EnergyConsumed EnergyConsumed Data source

Relationships Bus Bus_References Bus Name References

Bus_BusMotors Bus Name Bus Motor Name Number of Motors

Bus_Project Bus Name Project Name

Bus_Data Bus Name Bus_ID Manufacturer Date of 1st Re FuelType Passanger Seat Max Passenger

Bus_Motor_Data Motor Name Bus_Motor_ID Motor Type Manufacturer

BusMotor_References Bus_Motor_Name Reference

Bus_BusSpecialComponents Bus Name Bus Special Components Name Number

Bus_Special_Component_Data Bus Special Component Name Bus_Special_Component_ID Type Manufacturer

Bus_BusEnergyTransformer Bus Name Bus Energy Transformer Name Number

Bus_Energy_Transformer_Data Energy_Transformer_ID Energy Transformer Type Energy Transformer Name

Bus_BusStorageSystem Bus Name Bus Storage System Name

Bus_WorkshopRequirements Bus Name Workshop Requirement

Bus_Storage_System_Data Bus_Storage_System_Name Bus_Storage_System_ID Manufacturer Date of Production Workshop_Requirement_Data Workshop Requirement Id Workshop Requirement Name Description Safety Related

BusSpecialComponent_Refernces Bus_Special_Component Refernces

BusEnergyTransformer_Refernces Bus_Energy_Transformer Refernces

BusStorageSystem_Refernces Bus_Storage_System References

WorkShopReq_Reference Work Shop Requirements Reference

Relationships Project City_Data City Name Country Population Climate Topography Project_Cities Project_CitiesID ProjectID CityID FuelProductionPath Bus

Project_Data ProjectID Project Name Acronim FuelID ResearchObject

Country_Data ID Country

ProjectCities_Partner Project City Partner Partner type

Bus_Data Bus Name Bus_ID Manufacturer Date of 1st Registra FuelType

FuelPath_Data Fuel_Path_ID Fuel Path name Fuel type Project_Partner ProjectPartnerID ProjectID Partner name Partner Type

Project_Reference ProjectID ReferenceID

Reference_Data ReferenceID Reference Tiltle

Partner_Data PartnerID Partner Name Core Competence ContactID Description

Appendix 2: SUSI Manual

SUSI Sustainable Urban Transport System Investigation

SUSI v1.0 User Manual

Foreword

Foreword SUSI - Sustainable Urban Transport System Investigation - is a software-tool to compare the different usage schemes of alternative fuels and propose adequate solutions for fuel production and distribution. SUSI was developed by TFK and the project was initiated by the ECTOS project (Reykjavik, Iceland) and Vinnova (Swedish Agency for Innovation Systems). What is the motivation of SUSI? Alternative fuel well-to-wheel pathways differ in environmental, economical, technical and socio-economic performance; there is a need for a tool that will systemize the available data and put into use for decision makers. Furthermore, there is a need for a tool to collect and organize information and experiences coming from different projects concerning different fuels. What does SUSI offer? SUSI aims to help decision makers in the field of urban public transportation to find out which well to wheel pathway is best fulfilling the goals of their community. SUSI offers the structure of a dbase/Decision Support System; the structure is divided in two basic parts: -Descriptive Model – “Pedagogic Handbook”, which can be seen as a small “encyclopedia” concerning alternative fuels. -Well-to-Wheels pathway comparison tool: SUSI will compare the pathways – resource extraction, feedstock production and distribution, fuel production and distribution, and fuel consumption – and will recommend the most appropriate pathway. In the following figure the structure of SUSI is presented; data about the elements in the boxes is stored in the dbase and it is used accordingly by the Descriptive Model and the Well-to-Wheels pathway comparison tool. Ancillary Resources Possible Additions/upgrades

Feedstock Path

Fuel Path

End-Use Phase

Extraction

Resources

Resource Transportation

Production

Vehicle

Processing

Conversion

Treatment

…

…

Refining

Distribution

Production

…

Current Structure

Feedstock Transportation …

Emission & Cost calculations Human working hours potential

Possible Additions/upgrades

I

Foreword Basic features of SUSI : Flexible structure: the dbase is able to describe and store data for all alternative fuels and buses; Different User Profiles: the user of the dbase can simulate different locations by defining different user profiles. In the current version user profiles are used to set the production possibilities that exist at a location; in future versions it will be possible for the user to define more variables. Different Data Sets: since different source provide different data concerning emissions and economical values, SUSI gives the user the opportunity to choose between different data sets, but also define new sets that represent the user’s situation. Possible upgrades: SUSI is open for adjustments; future plans for the dbase include the calculation of human working hours potential that the implementation of a path will result, a more analytical economical analysis for the well-to-wheel path and the introduction of more decision criteria i.e. size of bus, topography, climate etc.

About this manual This manual is referring to SUSI v1.0; the first version of SUSI. In this manual SUSI v1.0 is going to be referred to as SUSI or dbase for simplicity reasons. This manual is also part of the Master Thesis: Development of Sustainable Urban Transport System Investigation, Decision Support System for the Usage of Alternative Fuels in Public Transportation; prepared by Sönke Behrends and Panagiotis Georgousis (there are some changes compared to the thesis version of the manual for keeping it up to date purposes). The purpose of the manual is to present the features of the dbase and to explain to the user how to use the tools that SUSI provides. For the best understanding of the features of the dbase it is recommended that the user will study the manual and in parallel use the software. For data filling it is essential that you have some experience on well to wheel analysis and life cycle studies. Information included in this manual are only for descriptive purposes of SUSI v1.0, information in the screenshots of SUSI v1.0 does not depict results or true facts, if not differently specified. For more details concerning the development and the features of SUSI you can contact: Sönke Behrends: [email protected] Panagiotis Georgousis: [email protected] Supervisor of the project: Magnus Blinge: [email protected]

II

Table of Contents

Table of Contents FOREWORD

I

TABLE OF CONTENTS

III

TABLE OF FIGURES

V

PART 1: INTRODUCTION

1

1.

Scope of SUSI

1

2.

Credits

1

3.

4.

Definitions 3.1 Definitions concerning dbase structure 3.2 Definitions concerning alternative fuel model System Requirements

1 1 3 3

PART 2: USER MODE – HOW TO USE SUSI

4

1.

Structure of the model

4

2.

Introduction Form

4

3.

Descriptive Model 3.1 Alternative Fuel Projects 3.1.1 Project Form Concept 3.1.2 Main Project Form 3.2 Alternative Fuel Buses 3.2.1 Bus Form Concept 3.2.2 Bus Form 3.2.3 Bus Workshop Requirements 3.3 Fuel Production – Feedstock Production 3.3.1 Fuel Production – Feedstock Production Concept 3.3.2 Fuel Production – Feedstock Production – Resources 3.4 Additional Features 3.4.1 Reference From 3.4.2 Partner Form 3.4.3 Contact Form

6 6 6 7 9 9 10 12 13 13 14 20 20 21 22

4.

Decision Support System Model 4.1 The DSS Concept of SUSI 4.1.1 Delimitation Process 4.2 Decision Factors 4.3 Decision Support System 4.3.1 User Profile Choice 4.3.2 Choose Data Set 4.3.3 Well-to-Wheels Results 4.4 User Profile Settings 4.5 Data Sets

23 23 23 24 25 25 26 27 29 32

III

Table of Contents 5.

Data Filling Mode 5.1 Add New Fuel Path 5.1.1 Setting the Percentage of Feedstock Production 5.2 Edit an existing Fuel Path 5.3 Add and Edit Project related data 5.4 Data Filling Issues 5.4.1 Cost 5.4.2 Functional units

PART 3: DOCUMENTATION

37 37 39 40 41 41 41 42

43

1.

Emission and Cost Calculations 1.1 Tables 1.2 Queries 1.3 Macros

43 43 44 46

2.

UserData Import/Export 2.1 Tables 2.2 Queries 2.3 Macros 2.4 Buttons

47 47 47 47 48

3.

Fuel-Path-Delimitation 3.1 Tables 3.2 Queries 3.3 Macros

48 49 49 50

IV

Table of Figures

Table of Figures Figure 1: General Structure of the Model ........................................................................... 4 Figure 2: Introduction form ................................................................................................ 5 Figure 3: Structure of Project form..................................................................................... 6 Figure 4: Introduction to Project form ................................................................................ 7 Figure 5: Project form......................................................................................................... 8 Figure 6: Structure of Bus form ........................................................................................ 10 Figure 7: Introduction to Bus form ................................................................................... 10 Figure 8: Bus form ............................................................................................................ 11 Figure 9: Bus Traction Module form ................................................................................ 12 Figure 10: Workshop Requirements form ........................................................................ 13 Figure 11: Structure of Fuel Supply.................................................................................. 14 Figure 12: Example Data for Structure of Fuel Supply .................................................... 14 Figure 13: Introduction to Fuel Production form.............................................................. 15 Figure 14: Fuel Data from................................................................................................. 16 Figure 15: Fuel Path (without emission data) form .......................................................... 17 Figure 16: Fuel Path sub-form (2nd Register) ................................................................... 17 Figure 17: Fuel Path Process form.................................................................................... 18 Figure 18: Feedstock Path (without emission data) form ................................................. 18 Figure 19: Feedstock Path Process (without emission data) form.................................... 19 Figure 20: Resource Data (without emission data) form .................................................. 20 Figure 21: Reference form ................................................................................................ 21 Figure 22: Partner Data form ............................................................................................ 21 Figure 23: Contact Data form ........................................................................................... 22 Figure 24: Delimitation Process........................................................................................ 24 Figure 25: Decision Factor form....................................................................................... 24 Figure 26: User Profile Choice form ................................................................................ 26 Figure 27: Data Set Choice form ...................................................................................... 27 Figure 28: Well-to-Wheels Results form.......................................................................... 27 Figure 29: Fuel Path Emissions Data................................................................................ 28 Figure 30: User Profile Settings form............................................................................... 30 Figure 31: City Data form................................................................................................. 31 Figure 32: Data Set Choice - Data Filling Mode form ..................................................... 33 Figure 33: Data Set form................................................................................................... 34 Figure 34: Fuel Path Process Data References form ........................................................ 35 Figure 35: Create New Data Set form............................................................................... 36 Figure 36: New Data Set Name form ............................................................................... 36 Figure 37: Choose Data Set - Data Filling Mode ............................................................. 37 Figure 38: Data Filling W-t-W form................................................................................. 39 Figure 39: Fuel Path Data form (2nd register) ................................................................... 39 Figure 40: Control 1: Percentage of Feedstock Production .............................................. 40 Figure 41: Data Filling Project Related Data.................................................................... 41

V

Part 1: Introduction

Part 1: Introduction 1.

Scope of SUSI

The purpose of the SUSI is to support politicians, local authorities and public transport operators that are considering an implementation of an alternative fuel bus system. SUSI consists of 1) a descriptive model which presents the functionalities of different alternative fuel systems and provides an overview about ongoing and finished projects concerning alternative fuels and 2) a Decision Support System which compares alternative fuel path usage schemes. The purpose of SUSI is to help organise and systemise data coming from different LCA and Well-to-Wheel studies concerning the usage of alterative fuels. SUSI can use this data in order to provide general information but also to “propose” the most suitable alternative fuel – fuel production path and bus that suits best the user profile that the user has chosen (all phrasing in italics is defined in section 3). The structure of SUSI v1.0 allows it to be used as a Well-to-Wheel model, but this is not its main purpose. SUSI is developed using Microsoft Access 2002.

2.

Credits

SUSI was developed by Chalmers University of Technology and TFK Institutet för transportforskning (Transport Research Institute Gothenburg, Sweden). Co-financers of the model development are Vinnova, the Swedish Agency for Innovation Systems and ECTOS (Ecological City TranspOrt System); a European Union project initiative to test three fuel cell buses in public transportation in Reykjavik, Iceland. SUSI was developed as a Master Thesis of Sönke Behrends (MSc in Transportation Management and Logistics, Chalmers University of Technology); and Panagiotis Georgousis (MSc in Logistics and Transportation Management, School of Economics & Commercial Law – Handelshögskolan, Göteborg University). The master thesis commenced June 2004 and was concluded January 2005. Supervisor of the master thesis was Magnus Blinge and advisor Elisabeth Soerheim. The master thesis was conducted according to the endorsed rules and regulations of Chalmers University.

3.

Definitions

Before continuing further into the manual it is essential to give several definitions in order to make it easier for the user to understand the following parts of the manual.

3.1

Definitions concerning dbase structure

User: is the person or organization using SUSI to collect data.

1

Part 1: Introduction Administrator: also referred to as dbase administrator, is the person or organization that is responsible for updating the program, adding new features and providing the “user” with general assistance Since SUSI was developed in Access 2002 it is to the user’s benefit to be aware of the very basic elements of the software. Tables: A table is a collection of data about a specific topic, such as products or suppliers. Using a separate table for each topic means that you store that data only once. This results in a more efficient database and fewer data-entry errors. Queries: Queries are used to view, change, and analyze data in different ways. Queries can also be used as a source of records for forms, reports, and data access data. Forms: A form is a type of a database object that is primarily used to enter or display data in a database. You can also use a form as a switchboard that opens other forms and reports in the database, or as a custom dialog box that accepts user input and carries out an action based on the input. Sub-form: A sub-form is a form that is inserted in another form. The primary form is called the main form, and the form within the form is called the sub-form. A form/subform combination is often referred to as a hierarchical form, a master/detail form, or a parent/child form. Sub-forms are especially effective when you want to show data from tables or queries with a one-to-many retionship. Command Button or Button: Command buttons provide you with a way of performing action(s) by simply clicking them. When you choose the button, it not only carries out the appropriate action, it also looks as if it's being pushed in and released. Hyperlink: A hyperlink is a pointer from one object to another. The destination is frequently another Web page, but it can also be a picture, an e-mail address, a file (such as a multimedia file or Microsoft Office document), or a program. The hyperlink itself can be displayed as text or as a picture. Text box: You use text boxes on a form, report, or data access page to display data from a record source. List box: The list in a list box consists of rows of data. In a form, a list box can have one or more columns, which can appear with or without headings Combo box: A combo box is like a text box and a list box combined, so it requires less room. You can type new values in it, as well as select values from a list. The list in a combo box consists of rows of data. Rows can have one or more columns, which can appear with or without headings.

2

Part 1: Introduction Macro: Macros are a set of actions that are created to help with automating common tasks. By using groups of macros, you can perform several tasks at once.

3.2

Definitions concerning alternative fuel model

Alternative fuel: a liquid or gaseous non-petroleum fuel used to power transit vehicles. Usually refers to alcohol fuels, mineral fuel, natural gas, and hydrogen. Well-to-Wheel analysis: A rigorous examination of the entire process of creating and using fuels to provide power to the wheels of a vehicle, resulting in an assessment of requisite energy consumption and corresponding greenhouse gas emissions (according to GM W-to-W Europe study). W-to-W analysis is the outcome of the Wheel–to-Tank and Tank-to-Wheel analysis. Well-to-Tank: Accounting the energy consumption and greenhouse gas emissions over the entire fuel path from feedstock to fuel dispenser nozzle. Tank-to-Wheel: Accounting of the energy and greenhouse gas emissions resulting from moving the vehicle through its drive cycle. Structure of Fuel Supply: a term used in SUSI to describe all steps required for the production and distribution of an alternative fuel. It takes in consideration everything for the extraction of the resource to the dispensing of the fuel. Fuel Path: the sum of the processes that are needed in order to transform resource to the alternative fuel. Fuel Path Process: a specific process that is part of the fuel path. Requires Feedstock-s Feedstock: the energy input for the Fuel Path Process. Feedstock Path: the sum of the processes that are needed to transform resource to the feedstock required by the Fuel path processes Feedstock Path Process: a specific process that is part of the feedstock path. Requires resource-s. Resource: the energy input for Feedstock Path Process.

4.

System Requirements

Access 2000 or a later version should be installed. Hard disk space required depends on the size of the dbase. The size of SUSI v.1 application is approx. 20 Mb and in most cases will be delivered as a .zip file, which will contain SUSIv1.mde and all additional file and folders that SUSI requires in order to run properly.

3

Part 2: User Mode – How to Use SUSI

Part 2: User Mode – How to Use SUSI 1.

Structure of the model

Part 2 – User Mode of the manual is divided into four sections; 1. Structure of the mode (current section) 2. Introduction form: which explains to the user the functions of the first form that he/she will encounter when entering SUSI; 3. Descriptive Model: is the part of the dbase where the user can view and collect data concerning alternative fuels; 4. Decision Support System Model: is the tool that helps the user get an overview of the environmental and economic impact of implementing an alternative fuel well-to-wheel path. 5. Data Filling mode: where you will learn how to input data in the dbase. In the User Mode of SUSI, the user can add, delete and store data only to a certain level. In Figure 1, you can see the basic structure of the dbase taking the Introduction form as a starting point. Of course not all features of the dbase are depicted in Figure 1, for further information you can refer to the corresponding sections of the manual.

Figure 1: General Structure of the Model

2.

Introduction Form

This is the first form that the user will see when entering SUSI. The form can be seen in Figure 2. There are several options concerning general features; “Overview” is a .pps presentation showing the user the basic features of SUSI; “User Manual” is a .pdf read only file giving a detailed description of the dbase; “Learn about Alternative Fuels” provides several short clips or documents giving information about alternative fuels.

4

Part 2: User Mode – How to Use SUSI In the upper right corner of the form the user can see all the organizations that played a role in developing the dbase. The “Browse Database” section: this is the mode where the user can directly navigate through the database. By clicking on “Projects”, “Bus”, “Fuel Path” and “References” the user will have the option to sort the data or view everything that exists under each category. More detailed description will be provided in section 3. The “Decision Support System” section: “Decision Support System” will start the delimitation process; a process through which the user will find out the fuel-s and wellto-wheel path-s that are feasible according to his location characteristics. The process will be described in detail in section 4. The “Data Filling” section: This is the data entry mode of the dbase where the user or the administrator of SUSI are able to enter and change data. The “Well-to-Wheels Data” button will enable the user to add and edit data concerning the well-to-wheel path. The “Project Related Data” button will enable the user to add and edit data concerning alternative fuel projects. More detailed description will be provided in section 5.

Figure 2: Introduction form

5

Part 2: User Mode – How to Use SUSI

3.

Descriptive Model

The purpose of the Descriptive Model of SUSI is to present information concerning alternative fuels for use in the public transportation sector.

3.1 3.1.1

Alternative Fuel Projects Project Form Concept

The purpose of the “Project Form” is to present all projects concerning alternative fuel usage for public transportation, either on-going or completed. The user can inform him/her in detail or just retrieve general information concerning the project. Figure 3 depicts the total structure of the “Project Form”. The main concept is that each project has several partners and is located in one or more cities/sites. If the project is active in more than one city it is probable that there are city specific / local partners. The distinction is necessary as to help the user to identify the roles and the responsibilities of each partner. “Structure of Fuel Supply” refers to the city specific production of the alternative fuel, distribution of the fuel and the feedstock required for the production; and the bus used in the project (well-to-wheels). References in this point of the dbase refer to project specific articles, brochures, websites etc. The reference form is available in section 3.4.1.

Figure 3: Structure of Project form

6

Part 2: User Mode – How to Use SUSI

3.1.2

Main Project Form

By clicking on the “Projects” button in the “Introduction” form you will be directed to the “Introduction to Projects” form (Figure 4). From this form you can access the data that is included in the dbase concerning alternative fuel projects. “Introduction to Projects” form gives the possibility to the user to filter the data in the dbase concerning projects. There are four filtering options available: 1. “View all Projects” which actually applies no filter and the user can browse through all the registers; 2. “View specific project” combo box gives the option to view a specific project, first you have to choose the Project you wish to view and then press the “GO” button; 3. “Show all Projects dealing with: Fuel X” combo box will filter the dbase according to the alternative fuel of your choice, for example if you are interested only in projects concerning hydrogen then you have to set the combo box to “Hydrogen” and apply the filter by click on the “GO” button next to the combo box; 4. “Show all Projects dealing with: Research Object X” combo box will filter the dbase according to one of the six research object option that the dbase has. Again the filter in applied when clicking the adjacent to the combo box “GO” button.

Figure 4: Introduction to Project form

7

Part 2: User Mode – How to Use SUSI After one of the filter options is applied you will be directed to the main “Project_Data” form (Figure 5). Not all options seen on the screenshot of the form are available in SUSI v1.0.

Figure 5: Project form

Description of data elements a. Research Object: Identifies the type of the project. b. Project Coordinator & Contact Person: Provides the project leader and also the central contact person. c. Project description: This is a link to a new window providing a short description of the project. Objectives and the outlay of the project can be described in order to provide the user with background information. A print out version will be available. d. Project results: This is a link to a new window that will present an overview of the project results and a list of relevant publications. e. Budget details: This is a link to a new window presenting the organizations and companies that financed the project.

8

Part 2: User Mode – How to Use SUSI

f. Project Partner (1st register): This register provides a list of the general project “Partners” working on general project issues independent from the city/sites; the “Partner / Manufacturer” form will be further analyzed in a following section. g. Project Cities (2nd register): Provides a list of all cities involved in the project. From this register the user can retrieve detailed information concerning the city supply and the bus used.

and learn about the structure of fuel

h. City Partners (3rd register): Provides a list of city specific partner; e.g. local bus operator. i. Project References (4th register): Provides a list of all references relevant to this project.

3.2 3.2.1

Alternative Fuel Buses Bus Form Concept

The “Bus Form” is another way for the user to navigate through the database. The purpose of the form is to provide information concerning buses that run on alternative fuels. The concept behind this form enables the dbase to handle information relating to any kind of bus despite its configuration; i.e. hybrid technology. From this form the user can get information about the bus-manufacturer and a description of the bus, including technical components, references and a link to the projects in which the bus has been operating. Furthermore, information concerning workshop/maintenance requirements can be accessed from this form as well. The structure of the “Bus_Data” form is depicted in Figure 6.

9

Part 2: User Mode – How to Use SUSI

Figure 6: Structure of Bus form

3.2.2

Bus Form

By clicking on the “Bus” button in the “Introduction” form, SUSI will direct you to the “Introduction to Bus Form” form (Figure 7). This form has a similar function as the “Introduction to Projects” form. In this case there are three filter options: 1. “View All Buses” button: gives you the option to view all the registers in the dbase concerning buses using alternative fuels. 2. “View specific bus”: choose a specific bus out of the combo box and then press “GO” to view it. 3. “View all buses running on this fuel”: you can choose a fuel and then press “GO” to view all buses running on a specific alternative fuel.

Figure 7: Introduction to Bus form

After you apply one of the three filter options, you will be directed to the corresponding “Bus Data” form-s. A sample of the “Bus Data” form is provided in Figure 8.

10

Part 2: User Mode – How to Use SUSI

Figure 8: Bus form

Description of data elements a. Manufacturer: Provides a link to the form of the manufacturer of the bus. For further details go to section 3.4.2. b. Date of first registration: Date of first registration is a way to distinguish between different production series of the same bus. c. Description: This is a link to a new window providing a short description of specific characteristics of the bus. A print out version will be available. d. Technical & Performance parameters: This section provides the user with the physical dimensions and performance as well as with operating parameters. e. Bus Components (register 1 to 4): In these registers the user can find information about the bus components which are categorized into “Traction Modules”, “Storage systems”, “Fuel Cells Modules” and “Special components”. The dbase is able to handle all alternative fuel technologies, because every category (register 1 to 4) is adaptable to the number and type of components of the bus. By clicking on

the user can retrieve specific data about the

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Part 2: User Mode – How to Use SUSI bus component. Figure 9 provides a screen-shot of the “Bus Traction Module” as an example. f. References (register 5): Provides a list of all references relevant to the bus. g. Bus Projects (register 6): This register provides a list of projects in which the bus is operating. h. Workshop Requirements: This is a link to the “Workshop Requirement” form, which will be described in detail in section 3.2.3.

Figure 9: Bus Traction Module form

3.2.3

Bus Workshop Requirements

The user can reach this form from the main “Bus” form. The purpose of the “Bus Maintenance/workshop” form is to present the general requirements for maintaining the bus. Several of the requirements are Hydrogen driven and are similar for all buses running on hydrogen. These requirements are presented in the left register of the “Bus

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Part 2: User Mode – How to Use SUSI Maintenance/workshop” form as seen in Figure 10. The right register presents requirements that are depending only on the bus type.

Figure 10: Workshop Requirements form

3.3 3.3.1

Fuel Production – Feedstock Production Fuel Production – Feedstock Production Concept

This part of the dbase is giving information about the production and distribution of alternative fuels. In the graph below (Figure 11) the way that SUSI organizes the Fuel Supply (fuel production-distribution, feedstock production-distribution) is depicted. Before a fuel is available at the filling station many processes from the “well” of the resource to the “tank” of the vehicle are necessary. Therefore a "well-to-tank"-path consists of several processes that can be grouped into two main categories: • Fuel path processes: which constitute the Fuel Path; every process from the production site of the fuel to the vehicle tank. This includes the fuel production, storage and distribution. • Feedstock path processes: which constitute the Feedstock Path; every process from the extraction of the resources to the production of the Feedstock and its distribution. Both kinds of processes consume energy and produce emissions. Feedstock Path processes consume Resources, Fuel Path Processes consume Feedstock. In Figure 12 an example of how data is organized is depicted. In Figure 11 the Fuel Production and Distribution (also referred to as Structure of Fuel Supply) is taken as the starting point; of course it must be taken into consideration that every alternative fuel has one or more production and distribution paths.

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Figure 11: Structure of Fuel Supply

Figure 12: Example Data for Structure of Fuel Supply

3.3.2

Fuel Production – Feedstock Production – Resources

By clicking on the “Fuel Production” button on the “Introduction” form, the following form will appear (Figure 13).

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Figure 13: Introduction to Fuel Production form

Through the “Introduction to Fuel Production” form the user is able to filter the registers of the dbase concerning alternative fuel production, feedstock production and resources. From here you can start navigating through the dbase in order to retrieve data concerning the way that alternative fuels are produced, what kind of feedstock do the production processes need, how this feedstock is produced and finally what kind of resource the feedstock production requires. There are three filtering options: 1. “Fuel and Fuel Production”: in this combo box the user has to choose an alternative fuel and the press the adjacent “GO” button. SUSI will open the corresponding “Fuel Data” form, a screenshot is provided in Figure 14. This form provides information concerning the fuel and the ways it can be produced. By clicking on the magnifying glass button on the “Fuel Data” form SUSI will open the “Fuel Path” form from where you can see how the fuel is produced and move on to see what kind of feedstock is need and how it produced. 2. “Feedstock and Feedstock Production”: this filter gives the user the choice to sort the dbase registers concerning feedstock and feedstock production. Choose one of the options in the combo box and click on the adjacent “GO” button. 3. “Resource”: this option enables the user to sort the registers concerning the resources.

Note: in SUSI v1.0 there are two sets of the fuel path – feedstock path – resources forms; the set used in the descriptive model is without emissions and cost data and the set used in the DSS part of the dbase is with emission and cost data. The reason of the distinction is that emission and cost data are data set specific (view section 4.5 and 5). The set of forms including the emission and cost data can be viewed through the DSS part of the dbase.

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Part 2: User Mode – How to Use SUSI After one of the filtering options is applied in the “Introduction to Fuel Path” form SUSI will direct you to the corresponding “Fuel Data” form Figure 14.

Figure 14: Fuel Data from

In the “Fuel Data” form the user can find a sub-form which has a list of all the fuel production paths (at least the ones that are inputted in dbase). By clicking on the “magnifying glass” button SUSI will direct you to the corresponding form of the fuel production path. A sample screen shot is provided by Figure 15. The “Fuel Production” form is the first, out of six steps, of the “Structure of Fuel Supply” as described in Figure 11. In the first register if the sub-form of the “Fuel Production” form you can find the steps – fuel path processes – that the specific Fuel Path consist of; by clicking on the adjacent “magnifying glass” button you will be directed to the corresponding “Fuel Path Process” form (Figure 17). The “Fuel Path Process” form is the second step according to the “Structure of Fuel Supply” as described in Figure 11.

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Figure 15: Fuel Path (without emission data) form

Figure 16: Fuel Path sub-form (2nd Register), provides information concerning the feedstock each “Fuel Path Process” requires. By clicking on the blue arrow buttons next to the “Fuel Path Process” title you are able to scroll through the fuel path processes that comprise the Fuel Production Path. By clicking on the “magnifying glass” button next to the “Feedstock Path” you will be directed to the corresponding “Feedstock Path” form (Figure 18). “Feedstock Path” form is level 4 in Figure 11.

Figure 16: Fuel Path sub-form (2nd Register)

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Figure 17: Fuel Path Process form

Figure 18: Feedstock Path (without emission data) form

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Part 2: User Mode – How to Use SUSI The “Feedstock Path” form describes the Feedstock Production Path and in the sub-form the feedstock path processes are presented. By clicking on the “magnifying glass” button you will directed to the corresponding “Feedstock Path Process” form (Figure 19). “Feedstock Path Process” form is level 5 in Figure 11.

Note: In the case that the feedstock is electricity it is very common that the feedstock production path is the electricity production grid mix of a country. For country specific electricity production grid mix there is usually already organized data concerning resource usage and in general emission and cost values. So the Feedstock Production Path can be the same as the Feedstock Path Process.

Figure 19: Feedstock Path Process (without emission data) form

The “Feedstock Path Process” form includes information concerning the Feedstock Path Process; in the sub-form the resources that this Feedstock Path Process requires; by clicking on the magnifying glass you will be directed to the corresponding “Resource Data” form (Figure 20). The “Resource Data” form is level 6 concerning Figure 11.

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Figure 20: Resource Data (without emission data) form

3.4 3.4.1

Additional Features Reference From

The “Reference Data” form includes all information concerning references used for filling in data for the dbase. The form also contains information concerning the projects that the specific reference is related to. Links to the “Reference Data” form are found in several parts of the dbase but the form can also be accessed directly from the “Introduction” form by clicking on the “References” button. First you will be directed to the “Introduction to References” form where you can start your search by sorting out the registers concerning references.

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Figure 21: Reference form

3.4.2

Partner Form

“Partner Data” Form includes information concerning partners to projects. Partners are usually companies, research institutions, universities etc. The “Partner Data” form can be reached from several other forms giving information on projects, buses and bus components for example. In the form there is also a link to the contact person of the partner (view section 3.4.3 ). Figure 22 provide a screenshot of the “Partner Data” form.

Figure 22: Partner Data form

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3.4.3

Contact Form

The “Contact Data” form provides information about contacts of projects and partners. The purpose of this form is to provide a link for the user if he/she wishes get in touch with the project coordinator or a partner.

Figure 23: Contact Data form

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4.

Decision Support System Model

This part of the manual is dedicated to the DSS part of SUSI. After reading this section the user will be able to create new user profiles, change data sets, run the delimitation process and comprehend the results that SUSI provides. To begin with, what is the DSS model of SUSI? It is a tool to help understand the impact that the implementation of an alternative fuel usage scheme (alternative fuel production, distribution & usage) will have to the ecosystem and the economy. The results of the DSS tool depend on the quality of the data that are imported in the dbase; so the more accurate the data imported in the dbase the more accurate the results will be. There are three important definitions that the user of SUSI has to understand in order to successfully use the DSS tool; a) User Profile: do not confuse this with the user of SUSI (person or organization), user profiles are identities for a set of characteristics (User Profile Settings) created by the actual user of SUSI in order to simulate real case scenarios. For better understanding of the user profile notion view section 4.3.1. b) User Profile Settings: is the set of data characterizing the user profile; more about user profile settings and how they can be configured in 4.4. c) Data Set: is a group of data that provides the emission and cost values of the wellto-wheel path processes (Section 4.3.2 and 4.5).

Note: Although the User Profile Settings are unique for each User Profile, all User Profiles have access to all Data Sets.

Note: If you make a new entry in the dbase, in some cases you will have to refresh the other forms in order to use the new entries you made. This is done by clicking the “Refresh” button usually found on the upper right corner of the forms. The DSS tool will start after clicking on the “Decision Support System” button in the Introduction form (Figure 2, page4). In sections 4.1, 4.2 and 4.3 the DSS tool is described.

4.1

The DSS Concept of SUSI

The DSS tool of SUSI aims to answer the following question: “Which Well-to-Wheels path fits best the needs of my urban transportation system?” In the following sections the DSS concept of SUSI will be explained and its basic features.

4.1.1

Delimitation Process

The delimitation process is the heart of the DSS tool of SUSI. Figure 24 provides a description of the delimitation process. The dbase has several default Well-to-Wheel

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Part 2: User Mode – How to Use SUSI paths already stored in, if the user wishes to add extra paths that is possible (view section 5). After the user starts the delimitation process SUSI will choose only the W-to-W paths that correspond to the user profile settings and presents them in a list – the Result Form (Figure 28). Then the user can sort them according to several decision factors.

Figure 24: Delimitation Process

4.2

Decision Factors

The most important part of a DSS tool is the decision factors; the factors or parameters according to which the system will sort the outcomes of a process. In the case of SUSI v1.0 there are four categories of decision factors; Global Environmental, Regional Environmental, Local Environmental, Economical and Long Term Sustainability. According to these categories the user can sort and prioritize the solutions provided in the Results Form after the delimitation process. The “Factor Data” form (Figure 25) can be reached from the Introduction form (first form that appears after running SUSI) by clicking on “Decision Factors”. On the upper part of the form you can see the name of the decision factor, factor type follows (explained above) and there is also a description of the decision factor giving general information. In the case of the screenshot in Figure 25 the description box provides an explanation of how the global warming potential is calculated in SUSI. In the reference section you can find the source of the above data.

Figure 25: Decision Factor form

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4.3

Decision Support System

How to run the DSS tool: There are four basic steps to complete in order to run the DSS tool: a) Choose or create a user profile and configure the user profile settings (view sections 4.3.1 and 4.4) b) Choose, add or edit a Data Set (view section 4.3.2, 4.5 and 5.1). c) Run the delimitation process d) Sort results according to Decision Factors (view section 4.3.3 concerning the well-to-wheel results, view section 4.2 concerning Decision Factors). Here you can see a summary of the steps that are needed in order to run the DSS tool in SUSI (a “hands on” approach): Introduction form Æ click on “Decision Support System” Æ “User Profile Choice” form Æ choose user profile and click “Next” Æ “Data Set choice” form Æ choose data set and press “Next” Æ “Well-to-Wheels Results” form.

4.3.1

User Profile Choice

User Profiles, as explained before in section 4.1, are identities given to a set of characteristics (User Profile Settings) in order to simulate real case scenarios. According to the User Profile that is chosen SUSI will delimitate the Well-to-Wheel paths that are not feasible. At the Introduction form when clicking on “Decision Support System” button the DSS process begins; the first form that appears is the “User Profile Choice” Form (Figure 26: User Profile Choice form). In this form you have to choose a User Profile; by clicking on the arrows below the text box you can see the User Profiles that already exist in the dbase. There are four options after you select a User Profile: 1. “View and Edit User Profile”: by clicking on the button the dbase will direct you to the corresponding form of the User Profile Settings (Figure 30). How to configure the User Profile Settings and the impact of this configuration are explained thoroughly in section 4.4. 2. “Create New User Profile” : in case you want to create a new User Profile you have to click on the “Create New User Profile” button; SUSI will then direct you to a blank “User Profile Settings” form where you can add and configure the new User Profile; for details concerning the configuration read section 4.4. After you finish adding the new User Profile press the “Refresh” button in order for SUSI to update the current form with your latest additions. 3. “Next”: by clicking on the “Next” button SUSI will save your chosen User Profile and User Profile Settings and open the “Data Set Choice” form (Figure 27: Data Set Choice form). 4. “Back”: by click the “Back” button the form will close and you will be directed to the “Introduction form”.

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Figure 26: User Profile Choice form

4.3.2

Choose Data Set

A Data Set is a group of data that specifies the emission, energy consumption and cost values of all fuel path processes and feedstock path processes. Different LCA and Wellto-Wheel studies provide different results regarding the same process; furthermore users of SUSI might have their own values for a specific process. With SUSI the user can choose which set of data he/she wants to use. Data in Data Sets can come from a single or multiple sources, depending on the research needs of the user. After choosing a User Profile the “Data Set Choice” form appears (Figure 27: Data Set Choice form). From the combo box you can select the data set of your choice; right above the “Choose Data Set” combo box, the user profile that has been chosen can be seen. There are four options after you select a data set: 1. “View and Edit Data Set”: by clicking on this button you will be directed to the corresponding “Data Set” form (Figure 33). Refer to section 4.5, 5.1 and 5.2 concerning Data Set configuration. 2. “Create a new Data Set”: by clicking on this button the user is able to create a new data set. For details concerning this topic refer to section 4.5. 3. “Next”: by clicking on the “Next” button SUSI will start the delimitation process. In the “Well-to-Wheel Results” form the results from the delimitation process are depicted (Figure 28, refer to section 4.3.3) 4. “Back”: by clicking on the “Back” button SUSI will close the current form and return to the “User Profile Choice” form.

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Figure 27: Data Set Choice form

4.3.3

Well-to-Wheels Results

This section is dedicated to the “Well-to-Wheel Results” form (Figure 28). This form presents the results of the delimitation process and is the final step of the DSS tool of SUSI. The “Well-to-Wheel Results” will appear after you commence the delimitation process by clicking on the “Decision Support System” button on the Introduction form and choose a User Profile and a Data Set in the two following forms.

Figure 28: Well-to-Wheels Results form

In the upper part of the form you can see the user profile and the data set that you have chosen in order to run the delimitation process and to calculate the W-t-W results. The

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Part 2: User Mode – How to Use SUSI results in the beginning are not sorted, so they are in random order; later on, the manual will explain how to short and filter the results that SUSI provided. The W-t-W results are presented as follows: first the Fuel Type is defined, then the Fuel Path name (the way to produce the fuel) and then the Bus name. Further to the right you can find the different potentials, consumption of Non-renewable energy resources and the W-t-W cost (€/km). By clicking on the “?” buttons you can retrieve data concerning the item next to the button. By clicking on the titles of the decision factors (section 4.2) the “Decision Factor” form will pop up. The “?” button next to the Fuel Path name text-box opens the “Fuel Path Emission Data” form (Figure 29). In this form the emissions, cost and energy consumption results of the fuel path are presented (excluding the bus figures). From this form you can either go back to the “Well-to-Wheels Results” form (“Back” button) or continue to view the alternative fuel production path (“View Fuel Path” button). View section 3.3 in order to find out how you can navigate through this part of the dbase.

Figure 29: Fuel Path Emissions Data

Filtering & Sorting the Results: a) Filter according to fuel: if the case is that you wish to view results concerning only one fuel, then you have to choose the fuel in the “Filter according to fuel” combo box and click on the “apply” button; SUSI will apply the filter and present only the paths that refer to the fuel of your choice. Click on the “Back” button which is located next to the “Filter according to fuel” combo box and SUSI will display again all results. b) Sort Results by Impact Category: Choose the impact category you wish in the “Sort Results by Impact Category” combo box and click on the adjacent “Apply”

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Part 2: User Mode – How to Use SUSI button; SUSI will categorize the results in an ascending list according to the values they have in Impact Category you choose. For example if you choose as impact category “GWP” then the best fuel – fuel production path – bus combination will be the one with the least GWP effect.

View Local Results: If you press on the “View Local Emissions” SUSI will take you to the “Local Well-toWheel Results”; this form presents emissions produced by the process that the user profile considers as local. This choice is made while manipulating the user profile data in the Fuel Path and Feedstock Path forms (for details view section 4.4). Click on the “Back” button to return to the main results form. Saving Results and Reporting: In order to save your results click on the “Save Results” button on the bottom right side of the “Well-to-Wheel Results” form. The results will be saved in .xls format (MS Excel) and you can find them in the WtW-Results folder that you have also the SUSI access file. The name of the .xls file will be: WtW-Results_user profile name_data setname.xls SUSI also provides a report of your results. Click on the “View Report” button in the bottom right of the form and the report will appear in a new window; right click on the margin of the report window in order to print the report. After finishing viewing the results forms click on the “Back” button on the “Well-toWheel Results” form to return to the “Introduction” form.

4.4

User Profile Settings

In this section of the manual you will learn how to configure a User Profile; Figure 30 depicts the “User Profile Settings” form. When editing a user profile there are two main things that you should take care of: first define which feedstock paths the user has access to and second set which of the feedstock and fuel path processes have a local environmental impact to the user profile’s location. The configuration process is similar for an existing and a new User Profile. As mentioned before in section 4.3.1, in order to add or edit a User Profile first the “User Profile Choice” (Figure 26) form must be opened, either click on the “View and Edit User Profile” button or the “Add new User Profile” button; then the “User Profile Settings” form will appear (Figure 30). Start the configuration by giving the user profile a name; choose a city etc. In the description box you can enter general info concerning the profile.

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Figure 30: User Profile Settings form

• City: The user can choose a city for that SUSI shall find the best alternative fuel. By clicking the user can see the characteristics of the city, like population, climate, on topography and traffic conditions which are influencing the fuel consumption (Figure 31). Since there are no results available yet how and to what extent these factors influence fuel consumption of the buses, they are not yet considered in the calculations. However they should be considered in the future versions of SUSI.

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Figure 31: City Data form

• Number of vehicle km: Here the user can fill in the total number of vehicle km the bus fleet of the chosen city drives over the whole year. With this figure the total amount of needed fuel can be calculated, and by this also the needed amount of feedstock and resources. This information will enable the delimitation of W-t-W paths which require more feedstock than available at this location. This feature is not implemented yet. • Annual capital charge: The Annual capital charge is needed to calculate the costs of a W-t-W Path. Since they differ from country to country it is part of the user profile. This is not included yet in the cost calculations. • Available Feedstock Sources: In the first register of the sub-form you have to set what feedstock paths are available for the user profile. According to the selected feedstock paths of the user profile the DSS tool of SUSI will come up with the feasible alternative fuel well-to-wheel paths, which will be presented in the “Well-to-Wheel Results” form after you run the delimitation process.

Note: If the user profile has access to “Electricity Production – Grid Mix CountryX” then you have to input both “Electricity Production – Grid Mix” and “Electricity Production – Grid Mix CountryX” in the sub form “Available Feedstock Sources”. If you only enter “Electricity Production – Grid Mix” then SUSI will take the data from the user profile that was used last time. For example, if your user profile is simulating a municipality in Sweden then it will have access to “Electricity Production – Grid Mix Sweden”, then you have to input both “Electricity Production – Grid Mix” and “Electricity Production – Grid Mix Sweden”

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Part 2: User Mode – How to Use SUSI • Definition of “Local for User” In the second register of the sub-form you have to define which fuel path processes and which feedstock path processes are local for the User Profile, in order to define which processes have an impact on the location of the user. According to the processes that are marked as “Local for the User” the Local EP, AP, POCP and HTP are calculated and are presented in the “Well-to-Wheels Local Emission Results” form. In order to define a fuel path process as “Local for the User” do the following steps: “User profile Settings” form – “Definition of Local for User” sub-form Æ choose fuel path and click on the magnifying glass button Æ “Fuel Path Data” form – “Fuel Production & Distribution” sub-form Æ click on the appropriate check box in order to define the fuel path process as “Local for User”. In order to define a feedstock path process as “Local for the User” do the following steps: “User profile Settings” form – “Definition of Local for User” sub-form Æ “Available Feedstock Paths” sub-form (2nd register) Æ click on the magnifying glass of the appropriate Feedstock Path Æ “Feedstock Path Data” Æ click the appropriate check box in order to define the feedstock path process has as “Local for User”. Saving User Settings: When you are finished configuring the user profile settings you can click on “Back” button; SUSI will ask you if you want to save the changes you made or not. If you choose to save the changes, SUSI will create two Excel file in the “User Profile” folder (which is situated in the same folder as SUSI) and delete the previous user profile settings. The name off the .xls files is: UserProfileName_Feedstockpath_FeedstockPathProcess and UserProfileName_Fuelpath_FuelPathProcess. Then you will return to the “User Profile Choice” form.

4.5

Data Sets

Data Sets, as mentioned in the beginning of section 4 and section 4.3.2, are groups of data that provide the values for the well-to-wheel paths. The purpose of using data sets is that you can store different set of data for the fuel and feedstock path processes; data can come from one or more sources. This section only explains how to add a new data set and how to edit data sets in a basic level; for more details you can refer to section 5.1 and 5.2. How to edit an existing Data Set: In SUSI you can edit data sets in two ways; one via the Decision Support System mode and the other via the Data filling mode. What actually differs is the path you follow until you reach the forms form where you can edit the data sets. Via DSS:

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Part 2: User Mode – How to Use SUSI Introduction Form Æ click on “Decision Support System” Æ “Use Profile Choice” form Æ choose any user profile, click “Next” Æ “Data Set Choice” form Æ choose data set you want to edit, click on “View and Edit Data Set” Æ “Data Set” form Æ start editing Via Data Filling mode: Introduction Form Æ click on “Well-to-Wheels Data” button Æ “Choose Data Set / Data Filling mode” form (Figure 32)Æ choose a data set and click on the “Choose” button”Æ “Data Feeling W-t-W” form Æ click on “Show Data Set”Æ “Data Set” form. or Æ choose the element you wish to edit from one of the combo boxes and click on “EDIT”

Figure 32: Data Set Choice - Data Filling Mode form

Figure 33 provides a screenshot of the “Data Set” form. In the top of the form the name of the Data Set and a description is provided (since we are now in edit mode all fields can be edited). The sub-form has two registers: “Fuel Path Processes” and the “Feedstock Path Processes” register. Here the user can view and edit data concerning all processes.

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Figure 33: Data Set form

By clicking on the button with the book you will be directed to the corresponding “Fuel Path Process Data Sources” form. Depending on which register you are working in you will be directed either to the “Fuel Path Process Data & Sources” form or the “Feedstock Path Process” form. Figure 34 provides a screenshot of the “Fuel Path Process Data & Sources” form. In the “Fuel Path – Feedstock Path Process Data & Sources” forms you can find the name of the Data Set that you are working on, the name of the fuel path process or the feedstock path process and finally the emission types and the cost (Capex + Opex). The following fields can be filled in: • Value: value of emission type (gr) or cost (€) per MJ of fuel or feedstock produced. • Data Source: this is a look up from where you can choose a reference for the data source. By clicking on the “?” button you will be directed to the corresponding “Reference Data” form. If the reference does not exist click on the “Add new source” and add the reference. • Page: you can input the exact page from where the data concerning the value comes from. • Comment: add a comment concerning the source or/and data value.

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Figure 34: Fuel Path Process Data References form

How to add a new Data Set: When creating a new data set, SUSI provides the possibility that you can base the new data set on an existing data set, so there is no need to fill al the data elements from the beginning. There are two ways to add a new Data Set: Via the Decision Support System mode: Introduction form Æ click on “Decision Support System” buttonÆ “User Profile” form Æ chose User Profile, click “next” button Æ “Data Set Choice” form Æ click on the “Create a new data set” button Æ “New Data Set” form Æ select the already existing data set that you want to base the new data set on; if you wish to create a data set from the beginning choose the “BLANK” data set from the combo box in the form, click “next” button Æ “New Data Set Name” form Æ Type a name for the new data set and provide a general description and the basic sources that are going to be used in the new data set Æ click on the “Create new Data Set”. Via the Data Filling mode: Second: Introduction form Æ click on “Well-to-Wheels Data” button Æ “Data Set Choice / Data filling mode” form Æ click on “Create new data set” Æ “New Data Set”

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Part 2: User Mode – How to Use SUSI form Æ select the already existing data set that you want to base the new data set on; if you wish to create a data set from the beginning choose the “BLANK” data set from the combo box in the form, click “next” button Æ “New Data Set Name” form Æ Type a name for the new data set and provide a general description and the basic sources that are going to be used in the new data set Æ click on the “Create new Data Set”. After you add the new data set you can start editing it as explained in the previous part.

Figure 35: Create New Data Set form

Figure 36: New Data Set Name form

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5.

Data Filling Mode

Section 4 focuses more on how to run the DSS model of SUSI. This section will go deeper into how to enter data, add and edit fuel paths and will provide some tips on how to control the data filling process. After adding a user profile and data set, SUSI is ready to start the delimitation process; this means that SUSI will provide results according to the Fuel Production Paths that exist in the database and according to the user profile of and the data set of your choice. So, it might be the case that you want to add a Well-to-Wheels path (fuel production path and bus) or configure the data set.

Figure 37: Choose Data Set - Data Filling Mode

5.1

Add New Fuel Path

In case you want to test and compare a new fuel production path you have to add it in the dbase. Even if the new fuel production path resembles to a path that already exists in the dbase you have to add the new production path. Fuel production paths should not be edited since they are used by all user profiles for the delimitation process; what should be changed is the data set (emission and cost figures of the Fuel Paths). In order to add a new path the following steps have to be completed: a) Gather and organize the data you wish to import: before entering the alternative fuel path in the dbase you have to collect the required data and organize it in the sequence that SUSI requires. Figure 11 provides a good “map” in order to guide you in the data organizing process.* b) Check if the Alternative Fuel, Fuel Paths and Fuel Path Processes, Feedstock Path and Feedstock Path Processes, Resources you wish to input already exist in the dbase: if some of the above mentioned elements of the Fuel Path you wish to input already exist in the dbase, there is no need to input them again. You can find out if they are already in the dbase by: a) searching via the “Data Filling W-t-W 37

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c)

d)

e)

f)

form” (Figure 38) form in left section; b) via the filtering process for the fuel production offered from the descriptive model of the dbase. Choose and import a Data Set: In order to choose a Data Set open the “Data Filling W-t-W form” Form (Figure 38 – Introduction Form Æ click on “Well-toWheels data”) in the “Data Set” combo box you can select on of the existing Data Sets; click on the “Choose” button next to the combo box; SUSI will import the selected data set. If you wish to add a new data set refer to section 4.5. Input the new Fuel Production steps: in the “Data Filling W-t-W form” form there are several options of what you want to add; choose the appropriate button and SUSI will lead you to the corresponding form and you can add the missing fuel path step. After finishing with inputting the data click on “Back” button in order to return to “Data Filling W-t-W form” and continue likewise in order to fill in all missing fuel path steps. Click on the “Refresh” button each time you wish to add a new fuel path element and in order to continue with the next step.** Input the data set data: this can be done directly while adding the new fuel path steps. In case you wish to view and change the data of the existing fuel paths (including the ones you entered) you have to find the step you wish to configure searching through the combo boxes in the “Data Filling W-t-W form” form.** Save: When finished entering all missing steps click “Save Data Set” button on the “Data Filling W-t-W form” form and press “Back” button to go the Introduction form or press “Refresh” button in order to continue with the next step.

*Note: It is best to enter the missing steps backwards, meaning to start entering first the missing resource, then the missing feedstock path process, then… and finally the missing alternative fuel (start from step 6 towards step 1 plus the alternative fuel if you consider Figure 11).

**Note: The new Fuel Paths that you are going to add are going to be available for all other user profiles and data sets. The data in the data sets that you are going to input is going to be only available for the data set that you are working on.

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Figure 38: Data Filling W-t-W form

5.1.1

Setting the Percentage of Feedstock Production

There is a case that the feedstock for a fuel path process is produced by two or more feedstock paths; thus you have to set the percentage of feedstock that each feedstock path produces in the “Fuel path Data” form (2nd register) as seen in Figure 39. The value of the text box can be between 0 and 1; the default value is 1.

Figure 39: Fuel Path Data form (2nd register)

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Part 2: User Mode – How to Use SUSI

SUSI v1.0 provides a control procedure for this option. By clicking on “Search for data entry mistakes” button in the “Data Filling W-t-W form” form, SUSI will search and find if there any mistakes concerning the percentage of feedstock produced. You will be directed to “Control 1: Percentage of Feedstock Production” form where you can find out if there are any mistakes. The “Fix Mistake” button will take you to the form where the mistake is located and a message box will provide you with further instruction in order to proceed. After making the appropriate changes press “Back” button in the form you made the corrections and then in the “Control 1: Percentage of Feedstock Production” form click on the “Apply Corrections” button in order for SUSI to check the changes made. Repeat the process until no mistakes are found and then press the “Back” button to return to the “Data Filling W-t-W” form.

Figure 40: Control 1: Percentage of Feedstock Production

5.2

Edit an existing Fuel Path

To configure an existing fuel path you have to take the following steps: a) Gather and organize the data you wish to import: same as in section 5.1. b) Choose and import a Data Set: In order to choose a Data Set open the “Data Filling W-t-W form” form (view section 5.1), in the “Data Set” combo box you can view the data sets that already exist, select the Data Set of your choice and then click the “Choose” button next to the combo box; SUSI will import the selected data set. If you wish to add a new data set view sections 4.5 and 5.1. c) Configure the Data Set: at the “Data Filling W-t-W form” form, you can find all the existing Fuel Paths and Fuel Path Processes, Feedstock Paths and Feedstock Path Process; choose the item you want to configure and press the adjacent “Edit” button to open the corresponding form. Make the changes you wish and click the “Back” button. d) Save: Click “Save Data Set” button on the “Data Filling W-t-W” form.

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Part 2: User Mode – How to Use SUSI

5.3

Add and Edit Project related data

Through the “Add & Edit Project Related Data” form (Figure 41 – Introduction form Æ click on “Project Related Data”) you can add and edit data concerning alternative fuel projects and background information for the DSS tool of SUSI. The form is quite simple to use; all you have to do is choose the data elements that you wish to add or edit and find the appropriate field in one of the combo boxes and then click on the “EDIT” or “ADD” button. In order for you to be able to add or edit this data fields you should be familiar with section 3 of the manual.

Note: The “ADD” button will open a blank form of the project, partner, contact, etc that you want to add; so you will have to add all the data elements. If you want to add a specific data element, say for example a new telephone number for an existing contact, then you will have to find the contact name in the corresponding combo box and then click on “EDIT” and add the missing data.

Figure 41: Data Filling Project Related Data

5.4 5.4.1

Data Filling Issues Cost

Costs are only considered for the fuel path processes. Since the feedstock paths are mostly not in the responsibility of the cities, bus operators, etc, cost for the feedstock path processes are not relevant. The final cost of a feedstock path is in most cases in market prices, like for grid mix electricity or natural gas from a certain location. 41

Part 2: User Mode – How to Use SUSI

The cost of a fuel that is produced by a certain fuel path are calculated with following parameters: • Capex + Opex of a fuel path process This parameter represents the capital and operational cost of the fuel path process to produce 1 MJ of the final fuel • Cost of feedstock Each process consumes feedstock, creating following cost: The amount of feedstock needed times the feedstock price Well-to-Wheel cost: Besides the cost for the fuel, the operational cost and the fuel consumption of the bus have to be considered. The final WtW cost is: Fuel cost [€/MJ] * Fuel consumption [MJ/km] + Capex and Opex of the bus [€/km] = WtW Cost [€/km]

5.4.2

Functional units

Energy consumed:

MJex/MJf (MJ expended to process/produce 1MJ of the fuel)

Emissions:

g/MJf (g of the substance emitted to process or produce 1MJ of the fuel)

Cost:

€/MJf Ù €/GJ (for fuel and feedstock) €/km (Bus and final Well-to-Wheel cost)

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Part 3: Documentation

Part 3: Documentation The documentation of SUSI that is provided here was prepared for a previous version of the model. So there are some differences. In case you wish to learn more about how the system works contact the developers.

1.

Emission and Cost Calculations

The way that SUSI v1.0 calculates emissions and cost will be described in following sections. The tables, queries and macros of the dbase will be introduced and the manual will explain their functions.

1.1

Tables

Basic Data •

Fuel Data Hydrogen, CNG, Diesel, etc.

• Feedstock Data Energy source for fuel production and distribution processes Electricity, natural gas for steam reforming • Resource Data Energy source for Feedstock production and distribution processes Natural Gas (Russia), Natural Gas (Middle East) for Natural Gas Fuel Path • Fuel Path Data Basic data about fuel path: Name, fuel type, description, etc. and emission data. The emission data is calculated by the model according to the fuel path’s processes (explained later Æ Queries) • Fuel_FuelPath This table defines by which fuel paths a fuel can be produced. • Fuel Path Process Data Basic data about fuel path process: Name, fuel, description, etc. and emission data. The emission data of the process is basic data, not calculated. The emission data only represents the emission directly related to the process, emissions from the needed feedstock are excluded here (Æ Table Feedstock data) •

FuelPath_FuelPathProcess (m-n)

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Part 3: Documentation In this table the needed processes are allocated to the fuel paths. • FuelPathProcess_Feedstock (m-n) This table defines which feedstock and how much is consumed by the fuel path process. • Feedstock Path Data Basic data about the feedstock: Name feedstock, description, etc. and emission data as well as cost. The emission data is calculated by the model according to the feedstock path’s processes (explained later Æ Queries). The cost of the feedstock will not be calculated by the model according to the steps, since they are represented by market prices. • Feedstock_FeedstockPath (m-n) This table defines by which feedstock path a feedstock can be produced. • FeedstockPath_FeedstockPathProcess (m-n) In this table the needed processes are allocated to the feedstock paths. • Feedstock Path Process Data Basic data about fuel path process: Name, fuel, description, etc. and emission data. The emission data of the process is basic data, not calculated. • FeedstockPathProcess_Resource This table defines which resource and how much is consumed by the feedstock path process. • FuelPath_FuelPathProcess_Feedstock_FeedstockPath This table defines how the feedstock consumed by a fuel path is produced, meaning by which feedstock path.

1.2

Queries

• Calculate_FeedstockPathEmissions Calculates the sum of the emission figures of each process of a feedstock path. The result is a table of the total emissions of each feedstock path. This is saved in table “FeedstockPathEmissions_Data” created by the query. • Calculate_FeedstockPathEmissions_Local See above, here only the processes are considered that were set to “Local for User”. This is saved in table “FeedstockPathEmissions_Data_Local” created by the query. • Calculate_FeedstockPathEmissions_Local_Null In the cases where there are feedstock path for which no process is considered as local, there would be no entry for that feedstock path in the table 44

Part 3: Documentation “Calculate_FeedstockPathEmissions_Local” created by the query above. If there is no entry for a feedstock path the calculations of Fuel Path emissions that use this feedstock would be impossible. Therefore this query sets the emissions value for the feedstock paths that have no processes considered as local to zero and appends the data to the table “FeedstockPathEmissions_Data_Local”. • Calculate_FeedstockPath_ResourceEnergyDemand Calculates the sum of the resource energy demand of each process of a feedstock path. The result is the total resource energy demand of each feedstock path. This is saved in table “FeedstockPath_ResourceEnergyDemand” created by the query. This cannot be done in the “Calculate_FeedstockPathEmissions”-query. Because the feedstock path process is connected to the resources via a many-to-many-relation, the emissions would be added up more than only once in the case the feedstock path process has more than one resource. • Calculate_FuelPathData_FeedstockEnergyDemand Calculates the sum of the feedstock energy demand of each process of a feedstock path. The result is the total feedstock energy demand of each fuel path. This is saved in table “FuelPathData_FeedstockEnergyDemand” created by the query. • Calculate_FuelPathEmissions_from_Feedstock This query calculates the total emissions of a fuel path from its consumed feedstock by summing up the feedstock emissions of each fuel path process. The feedstock-emissions of a fuel path are the product of the “FeedstockPathEmissions_Data” (calculated in query “Calculate_FeedstockPathEmissions”) and the feedstock energy demand of the fuel path process. The data is saved in the table “FuelPathEmissions_from_Feedstock” created by the query. • Calculate_FuelPathEmissions_from_Process This query calculates the total emissions of a fuel path from its fuel path processes by summing up the emissions of each fuel path process. The data is saved in the table “FuelPathEmissions_from_Process” created by the query. • Calculate_FuelPathEmissions_from_Process_Local See above, here only the processes are considered that were set to “Local for User”. This is saved in table “FuelPathEmissions_from_Process_Local” created by the query. • Calculate_FuelPathEmissions_from_Process_Local_Null In the cases where there are fuel paths for which no process is considered as “local for the user”, there would be no entry for that feedstock path in the table “Calculate_ FuelPathEmissions_from_Process_Local” created by the query above. If there is no entry for a fuel path the calculations of Fuel Path emissions would not be impossible. Therefore this query sets the emissions value for the fuel paths that have no processes considered as local to zero and appends the data to the table “FuelPathEmissions_from_Process_Local”.

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Part 3: Documentation

• Calculate_FuelPathEnergyConsumption_by_Resource This Query calculates the amount of energy of each resource consumed by the fuel path. The data is saved in the table “FuelPath_ResourceEnergyConsumption”. • Update_FeedstockPathData This Query updates the emission data of the feedstock path to the data of the table “FeedstockPathEmissions_Data” that was created by the query “Calculate_FeedstockPathEmissions”. The energy demand is updated to the data of the table “FeedstockPath_ResourceEnergyDemand” that as created by the query “Calculate_FeedstockPath_ResourceEnergyDemand” • Update_FuelPathData This table updates the emissions data of the fuel path to the total emissions, calculated by adding the data from the table “FuelPathEmissions_from_Process” and “FuelPathEmissions_from_Feedstock”, created by queries. • Update_FuelPathEmissions_from_Process This query updates the feedstock energy demand of the fuel path to data calculated in the query “Calculate_FuelPathData_FeedstockEnergyDemand”.

1.3

Macros

These macros run several queries in order to update all calculations. This is necessary if emissions- and energy data was changed or if processes were added/deleted. The order in which the queries are executed is important. •

Update_FeedstockPathData 1. Calculate_FeedstockPathEmissions 2. Calculate_FeedstockPath_ResourceEnergyDemand 3. Calculate_Feedsotck_Path_Emissions_Local 4. Calculate_Feedsotck_Path_Emissions_Local_Null 5. Update_FeedstockPathData

•

Update_FuelPathData 1. Calculate_FuelPathData_FeedstockEnergyDemand 2. Caluculate_FuelPathEnergyConsumption_by_Resource 3. Calculate_FuelPathEmissions_from_Feedstock 4. Calculate_FuelPathEmissions_from_Process 5. Calculate_FeedstockPathEmissions 6. Update_FuelPathEmissions_from_Process 7. Update_FuelPathEmissions_from_Process_Local 8. Update_FuelPathEmissions_from_Process_Local_Null 9. Update_FuelPathData

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Part 3: Documentation

2. 2.1

UserData Import/Export Tables

These tables store the Fuel Path- and Feedstock path data that was imported. • IMPORT_FuelPathProcess_Data • IMPORT_FuelPathProcess_Feedstock • IMPORT_FeedstockPathProcess_Data • IMPORT_FeedstockPathProcess_Resource • IMPORT_FeedstockPath_FeedstockPathProcess • IMPORT_FuelPath_FuelPathProcess

2.2

Queries

These Queries update the existing fuel path- and feedstock path process data tables, that are used for the calculations, to the imported data. • Update_FuelPathProcessData_to_ImportData • Update_FuelPathProcessFeedstock_to_ImportData • Update_FuelPath_FuelPathProcess_to_ImportData • Update_FeedstockPathProcessData_to_ImportData • Update_FeedstockPathProcessResources_to_ImportData • Update_FeedstockPath_FeedstockPathProcess_to_ImportData

2.3

Macros

• Delete_Import_ProcessDataTables This macro deletes the tables where the imported data is stored. This is necessary to import new data, because in this process the IMPORT-Tables are created again. • Update_ProcessData_to_ImportProcessData This macro runs the queries to update the process data to the imported data. o Update_FuelPathProcessData_to_ImportData o Update_FuelPathProcessFeedstock_to_ImportData o Update_FeedstockPathProcessData_to_ImportData o Update_FeedstockPathProcessResources_to_ImportData o Update_FuelPath_FuelPathProcess_to_ImportData o Update_FeedstockPath_FeedstockPathProcess_to_ImportData After that the Fuel Path Data and Feedstock Data are calculated using the updated data by the following macros: o Update_FeedstockPathData o Update_FuelPathData

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Part 3: Documentation

2.4

Buttons

•

Save User Settings VBA-Code for Exporting Process Data Tables o Export Table “FuelPathProcess_Data” into excel-table “USERNAME_FuelPathProcessData” o Export Table “FuelPathProcess_Feedstock” into excel-table “USERNAME_FuelPathProcessFeedstock” o Export Table “FeedstockPathProcess_Data” into excel-table “USERNAME_FeedstockPathProcessData” o Export Table “FeedstockPathProcess_Resources” into excel-table “USERNAME_FuelPathProcessResource” o Export Table “FuelPath_FuelPathProcess” into excel-table “USERNAME_FuelPathProcess_FuelPathProcess” o Export Table “FeedstockPath_FeedstockPathProcess” into excel-table “USERNAME_FeedstockPath_FeedstockPathProcess”

•

Import User Data: GO-Buttons 1. Macro “Delete_Import_ProcessDataTables” 2. VBA Code for Importing Process Data Tables o Import excel-table “USERNAME_FuelPathProcessData” into Table “IMPORT_FuelPathProcess_Data” o Import excel-table “USERNAME_FuelPathProcessFeedstock” into Table “IMPORT_FuelPathProcess_Feedstock” o Import excel-table “USERNAME_FeedstockPathProcessData” into Table “IMPORT_FeedstockPathProcess_Data” o Import excel-table “USERNAME_FeedstockPathProcessResource” into Table “IMPORT_FeedstockPathProcess_Resource” o Import excel-table “USERNAME_FuelPathProcess_FuelPathProcess” into Table “IMPORTE_FuelPathProcess_FuelPathProcess” o Import excel-table “USERNAME_FeedstockPath_FeedstockPathProcess” into Table “IMPORT_FeedstockPath_FeedstockPathProcess” o 3. Macro “Update_ProcessData_to_ImportProcessData”

3.

Fuel-Path-Delimitation

These functions delete those fuel paths from the total list of all fuel paths that are available to the user.

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Part 3: Documentation

3.1

Tables

• Fuel_Path_USER Includes all Fuel Paths that are available to the user. First, this table is created by a query, making a copy of all existing fuel paths, then the fuel paths that use feedstock paths that are not available to the user are deleted from this table. • Feedstock_Path_NOT_User Includes all the feedstock paths that are NOT available to the user. First this table is created by a query, making a copy of all existing feedstock paths, then the feedstock paths that are chosen by the user as available are deleted from this table. • User_Feedstock_Path This table includes the feedstock paths that have been chosen by the user as available.

3.2

Queries

• Create_FuelPath_User_Table This Query creates a copy of the table “Fuel Path Data” and names it “Fuel_Path_User”. It contains all existing Fuel Paths. • Create_FeedstockPath_Not_User_Table Creates a copy of the table “Feedstock Path Data” and names it “Feedstock_Path_NOT_User”. It contains all existing Feedstock Paths. • Delete_UserActive_FeedstockPath_FROM_FeedstockPath_NOT_User Table FeedstockPath_NOT_User – Table UserActive_FeedstockPath This Query deletes all the feedstock paths that are available for the user from the table FeedstockPath_NOT_User. After running this query the table FeedstockPath_NOT_User contains only the feedstock paths that are not available for the user. • FuelPath_Using_Feedstock_NOT_User This Query identifies all the fuel paths that use the feedstock paths that are not available for the user. • DELETE_FuelPath_Using_FeedstockPath_NOT_User_FROM_FuelPath_User The identified fuel paths in the Query FuelPath_Using_Feedstock_NOT_User are deleted from the Table FuelPath_User. The outcome of this Query is that the Table FuelPathUser only contains the Fuel Paths that have only those feedstock paths as energy input which have been set available by the user. Fuel paths that use feedstock paths that are not available for the user are excluded in this table. 49

Part 3: Documentation

• User_Well-to-Wheels This Query defines the well-to-wheel paths that are available for the user. It connects the available fuel paths with the buses and calculates emission data for the whole chain from feedstock production to the bus. This query is saved in the table User_Well-to-Wheels • Create_User_Well-to-Wheels_EnergyConsumptionByResource This Query calculates the resource consumption of the Well-to-Wheel Paths. It is saved in the table User_Well-to-Wheels_EnergyConsumptionByResource that shows the resource consumption of each resource that is used in the path. • Create_User_Well-to-Wheels_TotalEnergyConsumption This Query calculates the total amount of resource energy of each well to wheel path and creates the table “User_Well-to-Wheels_TotalEnergyConsumption” • Create_User_Well-to-Wheels_TotalRenewableEnergyConsumption This Query calculates the amount of renewable resource energy of each well to wheel path and creates the table “User_Well-to-Wheels_TotalRenewableEnergyConsumption” • Update_User_W-to-W_NonRenewables • Update_User_W-to-W_TotalEnergyConsumption • Update_User_W-to-W_TotalRenewableEnergyConsumption These Queries update the Table “User_Well-to-Wheel_Data” to the resource energy consumption values that were calculated in the queries before.

3.3

Macros

• Delimitate_FuelPaths_According_User Runs following queries o Create_FuelPath_User_Table o Create_FeedstockPath_Not_User_Table o Delete_UserActive_FeedstockPath_FROM_FeedstockPath_NOT_User o DELETE_FuelPath_Using_FeedstockPath_NOT_User_FROM_FuelPath _User o User_Well-to-Wheels o Create_User_Well-to-Wheels_EnergyConsumptionByResource o Create_User_Well-to-Wheels_TotalEnergyConsumption o Create_User_Well-to-Wheels_TotalRenewableEnergyConsumption o Update_User_W-to-W_TotalEnergyConsumption o Update_User_W-to-W_TotalRenewableEnergyConsumption o Update_User_W-to-W_NonRenewables

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