Coal-Fired Power Plants in the United States: Examination of the Costs of Retrofitting with CO2 Capture Technology and the Potential for Improvements in Efficiency (Original issue date December 2009)

Revision 1, January 29, 2010

DOE/NETL- 402/102309

Disclaimer This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed therein do not necessarily state or reflect those of the United States Government or any agency thereof.

COAL-FIRED POWER PLANTS IN THE UNITED STATES: EXAMINATION OF THE COSTS OF RETROFITTING WITH CO2 CAPTURE TECHNOLOGY AND THE POTENTIAL FOR IMPROVEMENTS IN EFFICIENCY

DOE/NETL-402/102309 January 29, 2010

NETL Contact: Christopher Nichols Situational Analysis & Benefits Division Office of Systems, Analyses and Planning

National Energy Technology Laboratory www.netl.doe.gov

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Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

Table of Contents TABLE OF CONTENTS .............................................................................................................. I  LIST OF FIGURES ..................................................................................................................... II  PREPARED BY .......................................................................................................................... IV  ACKNOWLEDGMENTS ............................................................................................................V  LIST OF ACRONYMS AND ABBREVIATIONS .................................................................. VI  1.  INTRODUCTION..................................................................................................................3  2.  METHODOLOGY ................................................................................................................4  2.1  DATA SOURCES.................................................................................................................5  2.1.1  Base References ...........................................................................................................5  2.1.2  Energy Velocity Suite ...................................................................................................5  2.1.3  GIS Data Sources .........................................................................................................5  2.2  VIABLE POPULATION ......................................................................................................12  2.3  MODEL DEVELOPMENT AND ANALYSIS ..........................................................................17  2.4  PHYSICAL SIZE AND COST SCALING................................................................................17  2.4.1  Let-Down Turbine ......................................................................................................19  2.4.2  CO2 Compression.......................................................................................................19  2.4.3  CO2 Scrubber Cost .....................................................................................................20  2.4.4  SO2 Removal..............................................................................................................21  2.4.5  NOx Removal .............................................................................................................23  2.4.6  Recirculating Cooling ................................................................................................23  2.4.7  Discounted Incremental Plant Units ..........................................................................24  2.4.8  Construction Difficulty Factors .................................................................................24  2.4.9  Additional Land Requirements ..................................................................................28  2.4.10  Water Availability ..................................................................................................29  2.4.11  Total Investment CAPEX .......................................................................................29  2.5  ESTIMATION OF GENERATION AND CO2 EMISSIONS BY VARIED CAPACITY FACTORS ....30  2.6  OPEX .............................................................................................................................30  2.7  PARASITIC LOAD.............................................................................................................32  2.8  LEVELIZED COST OF ELECTRICITY ..................................................................................33  2.9  CAPTURED AND MITIGATED CARBON COST ...................................................................33  2.10  EFFICIENCY ANALYSIS ....................................................................................................35  3.  RESULTS .............................................................................................................................37  3.1  CARBON CAPTURE RETROFIT..........................................................................................37  3.1.1  Carbon Capture Case Results....................................................................................39  3.1.2  Waxman-Markey Carbon Mitigation Case Results ...................................................40  3.1.3  Comparison with Conesville Study Results................................................................43  3.2  EFFICIENCY ANALYSIS ....................................................................................................44  3.3  REFURBISH/RETROFIT OPTION ANALYSIS .......................................................................47  3.4  SEQUESTRATION AVAILABILTY ANALYSIS ................................................................50  4.  LIMITATIONS AND RECOMMENDATIONS ..............................................................51  APPENDIX A. EV SUITE DATA ELEMENTS ......................................................................52 

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Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

List of Tables Table 1. Table 2. Table 3. Table 4. Table 5. Table 6.

Database and Model—Annotation and Parameter Elements ........................................... 4  NETL Generation Projections ....................................................................................... 12  Itemized FGD Capital Costs .......................................................................................... 22  Carbon Loading by Generation Type ............................................................................ 35  Results from the Conesville Study and CCM ................................................................ 43  Key Input Parameters from the Conesville Study and CCM ......................................... 44 

List of Figures Figure 1. Example MS Terraserver Imagery ................................................................................. 6  Figure 2. Example Google Maps Imagery (color) on a Terraserver Image Base .......................... 7  Figure 3. EIA Electricity Market Modules .................................................................................... 8  Figure 4. Water Availability .......................................................................................................... 8  Figure 5. NatCarb Datasets ............................................................................................................ 9  Figure 6. USGS Oil and Gas Production Dataset ........................................................................ 10  Figure 7. NatCarb Sequestration Quality ..................................................................................... 11  Figure 8. Distance to Sequestration Opportunities—Count of Plants ......................................... 14  Figure 9. Distance to Sequestration Opportunities—Generation Capacity ................................. 14  Figure 10. Population of Coal-Fired Power Plants ...................................................................... 15  Figure 11. Breakdown of Viable Population by Count of Plants ................................................ 16  Figure 12. Breakdown of Viable Population by Generation Capacity ........................................ 16  Figure 13. Retrofit Equipment Layout for Conesville Unit 5 ...................................................... 18  Figure 14. Let-Down Turbine Cost and Size Scaling .................................................................. 19  Figure 15. CO2 Separation and Compression Cost and Size Scaling .......................................... 20  Figure 16. CO2 Scrubber Cost and Size Scaling .......................................................................... 21  Figure 17. Current and Additional Recirculating Cooling Required to Retrofit All Units with 90% CO2 Capture and Compression at the Conesville Plant ................................................ 24  Figure 18. Complete Plant Retrofit .............................................................................................. 25  Figure 19. Example Showing 10 Percent Close-In Construction Difficulty and 10 Percent Landscape Construction Difficulty ....................................................................................... 26  Figure 20. Example Showing 30 Percent Close-In Construction Difficulty, 10 Percent Landscape Construction Difficulty ....................................................................................... 27  Figure 21. Example Showing 0 Percent Close-In Construction Difficulty, 0 Percent Landscape Construction Difficulty ......................................................................................................... 27  Figure 22. Example Showing 15 Percent Close-In Construction Difficulty, 0 Percent Landscape Construction Difficulty ......................................................................................................... 28  Figure 23. Additional Land Requirements................................................................................... 29  Figure 24. Fixed OPEX Cost Function ........................................................................................ 31  Figure 25. Variable OPEX Cost Function ................................................................................... 31  Figure 26. Feedstock OPEX Cost Function ................................................................................. 31  Figure 27. Parasitic Load Scaling for Carbon Capture Retrofit Components ............................. 32  Figure 28. LCOE Equation and Parameters from Conesville Study ........................................... 33  ii

Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

Figure 29. Captured and Mitigated Carbon Costs ....................................................................... 34  Figure 30. NETL 2020 Projected EMM Generation by Type. .................................................... 35  Figure 31. Cumulative Nameplate Capacity as a Function of CO2 Capture CAPEX.................. 38  Figure 32. Nameplate Capacity as a Function of CO2 Capture CAPEX by Unit ........................ 38  Figure 33. Cumulative Nameplate Capacity as a Function of CO2 Capture LCOE for Base Case ............................................................................................................................................... 39  Figure 34. Cumulative Nameplate Capacity as a Function of CO2 Capture Cost for Base Case 40  Figure 35. Cumulative Nameplate Capacity as a Function of CO2 Capture LCOE for WaxmanMarkey and No CO2 Credit Case .......................................................................................... 41  Figure 36. Cumulative Nameplate Capacity as a Function of CO2 Mitigation Cost for WaxmanMarkey and No CO2 Credit Case .......................................................................................... 42  Figure 38. Cumulative Nameplate Capacity as a Function of CO2 Mitigation Cost for WaxmanMarkey and CO2 Credit Case ................................................................................................ 43  Figure 39. Cumulative Nameplate Capacity as a Function of Average 10-Year Efficiency ....... 45  Figure 40. Cumulative Nameplate Capacity as a Function of ∆-TDE ......................................... 46  Figure 41. Cumulative Electricity Gain as a Function of ∆-TDE ................................................ 46  Figure 42. Cumulative Avoided CO2 as a Function of ∆-TDE.................................................... 47  Figure 43. Refurbish/Retrofit Options CAPEX Rate ................................................................... 49  Figure 44. Refurbish/Retrofit Options Generation Loss Rate ..................................................... 49  Figure 45. Years of Sequestration Capacity within 25 Miles ...................................................... 50 

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Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

Prepared by: Research and Development Solutions, LLC (RDS) Jeffrey Eppink and Michael Marquis Enegis, LLC Lynn Manfredo Science Applications International Corporation

DOE Contract #DE-AC26-04NT41817

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Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

Acknowledgments This report was prepared by Research and Development Solutions, LLC (RDS) for the United States Department of Energy’s National Energy Technology Laboratory. This work was completed under DOE NETL Contract Number DE-AC26-04NT41817, and performed under RDS Subtask 41817-402.01.01 The authors wish to acknowledge the excellent guidance, contributions, and cooperation of the NETL staff, particularly: Philip DiPietro, NETL Technical Monitor Christopher Nichols, OSAP, Situational Analysis and Benefits Division

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Coal-Fired Power Plants: Costs of CO2 Capture Technology and Improvements in Efficiency

LIST OF ACRONYMS AND ABBREVIATIONS AEP

American Electric Power

Btu

British Thermal Unit = 1055 Joules

CAPEX

Capital Expense

CCM

Carbon Capture Model

CO2

Carbon Dioxide

DOE

Department of Energy

EIA

Energy Information Administration

EV

Energy Velocity

EMM

Electricity Market Modules

FGD

Flue Gas Desulfurization

GIS

Geographic Information Systems

GW

Gigawatt

kW

Kilowatt

kWh

Kilowatt hour

LCOE

Levelized Cost of Electricity

MS

Microsoft

MW

Megawatt

MWh

Megawatt hour

NEMS

National Energy Modeling System

NETL

National Energy Technology Laboratory

NOx

Nitrogen Oxide

OPEX

Operating Expense

OSAP

Office of Systems, Analyses and Planning

Ppm

Parts Per Million

SO2

Sulfur Dioxide

TDE

Top Decile Average Efficiency

Ton

short ton = 2000 pounds

Tonne

metric ton = 1000 kilograms

USGS

United States Geological Survey

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EXECUTIVE SUMMARY Given the importance of coal to power generation in the United States, where coal-fired power plants supply almost 50 percent of the Nation’s electricity needs, examination of the costs and practicability for retrofit of existing pulverized coal power plants with CO2 capture technology is a valid exercise. To help elucidate this issue, this study defines a viable population of pulverized coal plants, which were examined individually to determine costs and space availability for retrofit. The effort was designed to assess coal-fired power plants in the U.S. relative to the cost and feasibility for retrofit with CO2 capture technology. The study comprised the development of a database and geographic information systems (GIS) modeling analysis of coal-fired power plants in the U.S. to conduct the assessment. The viable population for the analysis was defined as those active plants with a combined unit generation capacity greater than 100 MW, an average heatrate below 12,500 Btu/kWh, and a location within 25 miles of a potential carbon sequestration opportunity. The resultant population totals 738 units located in 324 plants with a total generation capacity of 282 GWs. The units were then evaluated individually. The analysis is based upon the NETL 2007 publication Carbon Dioxide Capture from Existing Coal-Fired Power Plants (Conesville Study) as a foundation for the application of carbon capture retrofit technology in terms of cost and layout. Absolute costs for each generation unit were calculated then levelized in terms of cost of post-retrofit electricity, cost per tonne CO2 captured, and cost per tonne CO2 mitigated. The analysis, like the Conesville Study, assumes constant coal. That is, plants will not burn more coal to generate the make-up power associated with the parasitic load of the retrofit. Central to the analysis is the quantitative GIS model, entitled the Carbon Capture Model (CCM). The CCM comprises programmatically linked databases, GIS map documents, and report spreadsheets that calculate capital expense (CAPEX), operating expense (OPEX), and parasitic load associated with retrofitted carbon capture technology. The model evaluates these parameters by scaling costs using the plant-specific parameters and algorithms derived based upon the Conesville Study. A GIS imagery analysis of each plant was conducted to modify construction costs due to specific site requirements by assigning construction difficulty factors to retrofit components. Cost-supply curves relative to the viable population were developed. Results of the CCM analysis modeled at an 85 percent capacity factor without make-up power indicate that, for the 10th percentile (28 GW) of the analyzed viable population, the total levelized CO2 capture cost would be about $34/tonne or less. The 50th percentile (138 GW) of the analyzed viable population can be retrofitted with a total levelized CO2 capture cost of about $41/tonne or less. To retrofit 90 percent of generation capacity (about 249 GW), the total capture cost would be about $57 per tonne or less. When make-up power is considered the mitigation costs are $107, $90 and $73/tonne for the 90th, 50th and 10th percentiles respectively. These figures do not include the transportation, storage and monitoring of the CO2 once it leaves the plant gate. Ancillary to the CCM was an analysis of historical unit operating efficiency and the affect on generation and CO2 emission should all units be brought up to the average 1

efficiency of the top decile of efficient units (TDE) by nameplate. Results indicate that if all units were brought up to the average efficiency of the top decile, over 273 million incremental MWh would be generated burning the same amount of coal. If generation were held constant over 320 million tonnes of CO2 would not be emitted. Making these efficiency improvements would yield the equivalent of almost 37 one-GW power plants operating at 85 percent capacity for one year. A set of five options was applied to the CCM population to ascertain the effects in terms of costs, generation, and carbon emission reduction. All options were considered at an 85 percent capacity factor and include CAPEX costs. The five options were: (1) no action, (2) refurbish to improve efficiency, (3) retrofit for carbon capture, (4) refurbish-thenretrofit, and (5) raze and build new supercritical pulverized coal plant with carbon capture. The CAPEX rate for Option 2 shows a constant rate of $67.00/tonne for those units operating below TDE. Option 3 shows a CAPEX rate for the 50th percentile at about $9.00/tonne. Option 4 reflects a higher cost of the refurbish-then-retrofit option, with the 50th percentile near $13.00/tonne. Option 5 presents brownfield development of new plants, where the 50th percentile is near $23.00/tonne. The generation loss rate for Option 2 shows no change relative to the base case. Option 3 reflects the significant parasitic load of the retrofit equipment, where the 50th percentile is near 0.4 MWh/tonne captured carbon. Option 4 shows the mitigated parasitic load due to refurbishment, with the 50th percentile near 0.3 MWh/tonne. Option 5 reflects a decreased parasitic load for brownfield development of new plants with carbon capture, where the 50th percentile is near 0.25 MWh/tonne. These results show that, assuming a plant is amortized, the refurbish-then-retrofit option is less expensive compared to new construction. The refurbish-then-retrofit option is more costly than performing a stand-alone refurbishment or retrofit, but there is significant mitigation of lost generation. It should be noted that this study provides an overview of the plant sites. It is not an engineering-level analysis of individual plants and does not address the consequences of design.

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1. INTRODUCTION The effort comprised the development of a database and geographic information systems (GIS) analysis of a defined population of coal-fired power plants in the U.S. to model the cost and assist in the assessment of the feasibility of retrofitting these plants with CO2 capture technology. In addition, an assessment of the impacts on generation, CO2 emission, and fuel consumption should all units be brought up to the average efficiency of the top decile of efficient units by nameplate was made. This report covers data sources, methodology employed, modeling and results.

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2. METHODOLOGY Fundamentally, this effort is based upon the NETL 2007 publication Carbon Dioxide Capture from Existing Coal-Fired Power Plants (Conesville Study) as a foundation for the application of carbon capture retrofit technology in terms of cost and layout. As a central part of the database and analysis effort, the Carbon Capture Model, (CCM) comprises programmatically linked databases, GIS map documents, and report spreadsheets that calculate capital expense (CAPEX), operating expense (OPEX), and parasitic load associated with retro-fitted carbon capture technology. Table 1 shows a listing of annotations and parameters developed for the database and model. Table 1. Database and Model—Annotation and Parameter Elements

CAPEX and General

CAPEX and General (cont’d)

·Plant\Unit Name

·Let-down Turbine Size and Cost

·Nameplate Capacity ·No. of Operating Units ·Plant Size ·Electricity Market Module ·Sequestration Distance ·Heatrate ·Efficiency ·Prime Mover ·Sub vs. Supercritical ·Net Generation ·Coal Type ·Coal Volume Purchased ·Energy Content in Fuel ·SO2 Control Equipment Presence ·SO2 Emission Rate ·Sulfur in Purchased Coal ·Emitted S ·Scrubbed S ·NOx Control Equipment Presence ·NOx Emission Rate ·CO2 Emissions & Rate

·Primary FGD ·Marginal FGD ·CO2 Absorber Equipment Cost ·NOx Equipment Cost ·Close-In Construction Difficulty ·Separation & Compression Size and Cost ·Required Recirc Water System ·Heat Generated /Hour ·Current Recirc Water System ·Additional Recirc Water System ·Water availability ·Additional Water System Cost ·Landscape Construction Difficulty

OPEX -Fixed Labor

-Variable -Feedstock -Total Variable Cost Parasitic -Parasitic SOX -Parasitic NOX -Parasitic Water -Parasitic load (other) -Total Parasitic Load

·No. Units Discount ·Total CO2 Capture Construction CAPEX ·Offsite Requirements ·Population Density ·Land & Rights ·Additional Land Cost ·Total CO2 CAPEX ·Unitized CAPEX

Pipeline construction and CO2 transport operating costs are not included in the study costs. Also, not included is the cost associated with CO2 storage.

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2.1

DATA SOURCES

This section provides information on the references, data sources used for the database, model and analysis. 2.1.1

Base References

In addition to the Conesville Study, additional references for cost and other information include: • • • • •

2.1.2

Cost and Performance Baseline for Fossil Energy Plants, (“Baseline Report”), DOE/NETL-2007/1281, Volume 1: Bituminous Coal and Natural Gas to Electricity, Final Report, Revision 1, August 2007 Pulverized Coal Oxycombustion Power Plants (Oxycombustion Report), NETL, Final Results, August 2007 Reduced Water Impacts Resulting from Deployment of Advanced Coal Power Technologies, (Water Impacts Report) NETL, Chris Nichols and Phil DiPietro, December 16, 2007 Water Requirements for Existing and Emerging Thermoelectric Plant Technologies, (Water Requirements Report) NETL Kristin Gerdes and Christopher Nichols, August 2008 (April 2009 Revision) Roadmap for Bioenergy and Biobased Products in the US (Bioenergy Roadmap study), Biomass Research and Development Technical Advisory Committee, 2009 Energy Velocity Suite

The primary source of data on physical plant parameters such as unit nameplate capacity, heat-rate, and emissions was Ventyx Corporation’s Energy Velocity (EV) Suite, a compilation of energy industry and market databases. Appendix 1 provides a detailed description of the EV data elements that were used in the database and is based on the parameters description from the EV Data Dictionary. The database contains ten years of historical data. To provide a more valid representation of plant operations, the model uses ten-year average values for, heatrate, operations, and emissions data. 2.1.3 2.1.3.1

GIS Data Sources Microsoft Terraserver-USA Imagery

The Microsoft TerraServer-USA Web site is one of the world's largest online databases, providing free public access to a vast data store of maps and aerial photographs of the United States. The TerraServer name is a play on words, with “Terra” referring to the “earth” and also to the terabytes of images stored on the site. Maps and images are supplied to Terraserver through Microsoft’s partnership with the U.S. Geological Survey. TerraServer imagery was used both as a primary source of power plant imagery and as a basemap on which to georegister more recent or higher resolution imagery if available through Google Maps. The MS Terraserver imagery is available as an open-source Windows Mapping Service and as a seamless imagery layer within ESRI ArcGIS. 5

Figure 1 shows an example of available MS Terraserver imagery of Plant 1726 AES Somerset in Barker, New York. Of the 290 plants analyzed for this effort, 250 had satisfactory (best available) imagery obtained through MS Terraserver.

Figure 1. Example MS Terraserver Imagery 2.1.3.2

Google Maps Imagery

Google Maps is a Google service, which, with its sister service, Google Earth, compiles imagery from a variety of sources, including MS Terraserver. Google Maps often provided the most recent, highest resolution imagery for sites in the project. Figure 2 presents an example of available Google Maps imagery from Plant 2351, Gulf Power Co Christ Plant in Pensacola, Florida. Google Maps is not available as an open-source Windows Mapping Service, requiring screen capture and georegistration, processes which were performed for this project. Note the color, screen-captured Google Maps imagery georeferenced to the underlying, black and white Terraserver imagery. Of the plants analyzed for this project, 40 had the best available imagery through Google Maps.

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Figure 2. Example Google Maps Imagery (color) on a Terraserver Image Base 2.1.3.3

Electricity Market Modules

As an organizational framework for analyzing the population of the power plants, the Energy Information Administration (EIA) Electricity Market Modules (EMM) of the National Energy Modeling System (NEMS) were used. The EMMs divide the country into 13 regions that reflect capacity planning, generation, transmission, and pricing of electricity. GIS polygons representing the EMMs were not available. As such, accurate analog polygons were created using GIS of the NEMS subregions upon which the EMMs are based. Figure 3 shows the 13 EMMs. The EMMs were also used to compile market profiles of generation type for determination of CO2 associated with make-up power. 2.1.3.4

U.S. Geological Survey Water Availability

Data on the renewable water supply was provided by the U.S. Geological Survey (USGS), 1984, National Water Summary 1983—Hydrologic Events and Issues: U.S. Geological Survey Water-Supply Paper 2250. Renewable water supply is defined as the sum of precipitation and imports of water, minus the water not available for use through natural evapotranspiration and exports. Renewable water supply is a simplified upper limit to the amount of water consumption that could occur in a region on a sustained basis. Figure 4 shows the USGS water availability data. The USGS data were used to assess relative water availability for coal plants.

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Figure 3. EIA Electricity Market Modules

Figure 4. Water Availability

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2.1.3.5

Status of Fresh Water Aquifers

The Bioenergy Roadmap study was used as a data source on the status of fresh water aquifers to further define those geographic areas with stressed or overpumped aquifers. Figure 4 shows these overpumped aquifers in relation to the USGS water availability data. These data were used to identify those plants in areas where further withdrawal from local aquifers is problematic. 2.1.3.6

NatCarb Saline Aquifers and Existing CO2 Pipelines

GIS data on saline aquifers acceptable for carbon sequestration and the network of existing CO2 pipelines was obtained from NETL’s NatCarb website www.natcarb.org. Figure 5 shows these data.

Figure 5. NatCarb Datasets 2.1.3.7

USGS Oil and Gas Fields

GIS data on existing oil and gas production was obtained from the USGS. A comprehensive, nation-wide GIS polygon set of oil and gas fields is not readily available. The USGS has published an oil and gas production map of the United States. This dataset consists of over one million ¼ mile cells attributed with the presence of oil production, gas production, oil and gas production, or dry field. Figure 6 shows the USGS oil and gas data.

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Figure 6. USGS Oil and Gas Production Dataset 2.1.3.8

NatCarb Sequestration Capacity

Data were available from NatCarb on volumes of CO2 able to be sequestered in oil and gas fields and saline aquifers. These data were compiled to calculate a total sequestration capacity density map. Figure 7 shows sequestration quality in units of millions of tonnes CO2/ km2. It should be noted that not all areas identified in the NatCarb and USGS sequestration opportunity datasets are shown as having sequestration capacity, which leads to differences between the two data sets. This source was used to evaluate space availability only, and not the costs associated with storage and measurement, monitoring and verification.

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Figure 7. NatCarb Sequestration Quality 2.1.3.9 NETL Projections of Effects of American Clean Energy and Security Act H.R. 2454 (Waxman-Markey) Because the generation profile in a carbon-constrained world would significantly differ from the current power generation makeup, the CCM uses projections created by NETL to represent a likely generation profile following passage of the proposed WaxmanMarkey climate change legislation. In general, the profile becomes enriched in renewables and is less dependent upon generation from fossil fuels. NETL modeled the possible effects of Waxman-Markey out to 2030 using the EIA NEMS. The power generation profiles under the Waxman-Markey bill—i.e. a scenario with climate change regulations in effect—is used to account for the “make-up” power costs associated with retrofitting existing PC plants with CO2 capture. The CCM uses year 2020 values and extracts a unique power generation profile and generation costs for each EMM. Table 2 shows NETL’s projected generation by type and electricity generation cost by EMM.

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Table 2. NETL Generation Projections 2020 Generation (10^9 KwH) EMM

  Coal 1 2 3 4 5 6 7 8 9 10 11 12 13

2.1.3.10

463.2 113.0 121.2 138.1 104.3 11.5 9.7 61.8 409.0 126.1 66.6 127.1 31.2

     Natural    Pumped    Nuclear   Renewables Petroleum Gas Storage 1.7 0.4 4.4 0.5 0.4 5.2 2.2 13.4 4.0 0.5 0.1 0.4 0.1

26.0 123.6 19.2 14.3 1.1 47.2 42.3 52.4 96.2 40.0 21.2 62.1 45.0

62.3 49.7 120.2 119.6 24.5 47.3 36.0 89.8 296.9 9.2 8.9 24.8 44.1

‐1.0 0.1 0.8 0.3 0.3 0.4 1.0 1.1 ‐2.4 0.0 0.1 ‐0.1 0.0

59.3 36.1 45.3 47.7 59.6 29.5 36.2 23.1 91.2 29.5 196.1 27.7 102.5

2020  Electricity  Price  (cents/KwH) 7.6 7.9 8.7 6.7 5.6 9.9 8.1 11.0 6.7 7.6 4.3 8.2 7.3

NETL Steam Pressure Data

The CCM uses NETL data on required unit steam pressure. These data were compiled in conjunction with a multivariate CFPP efficiency analysis presented at a government/industry workshop in July 2009 in Chicago, Illinois entitled “The Opportunity to Improve the Efficiency of Coal-fired Power Plants.” 2.1.3.11

2000 US Census

Population density data was provided by the 2000 US Census, made available as a GIS polygon layer through ESRI Data and Maps 9.2. Population density provides a guide as to the possible tolerance of the surrounding area for expansion of a power plant. 2.2

VIABLE POPULATION

The viable population for the study was initially defined to be operating U.S. coal-fired power plants greater than or equal to 100 MW total nameplate capacity with a weighted average heat-rate equal to or less than 12,500 Btu/kWh. This definition was refined to include a distance to sequestration opportunity criterion. The analysis began with a population of 1088 coal-fired power plants identified in the EV datasets. Of these, 647 are identified as “operating”, thereby excluding retired or planned power plants. These plants represent 511 GW. Of the 647 operating plants, 416 have a total nameplate capacity greater than or equal to 100 MW, representing 408 GW. Of these 416 plants, 28 plants have a weighted average heat-rate greater than 12,500 Btu/kWh, resulting in a viable population of 388 plants in the analysis, representing 323 GW. 12

This population was further refined to account for distance to sequestration opportunities. A GIS analysis of each power plant’s proximity to each of three sequestration opportunities: oil and gas fields, saline aquifers, and existing CO2 pipelines was performed. Provided that two points exist in the same coordinate space, the distance between them can be calculated in the GIS using simple trigonometric functions. Polygon datasets must be converted to points to calculate distances. USGS oil and gas dataset used in the analysis exists as a set of ¼ mile polygons, a set of polygon centroid points was created and used to calculate power plant distances. Because the NatCarb saline aquifer data exists as complex polygons, polygon nodes were converted to points. Power plants that fall within the border of a saline aquifer polygon were assigned a distance of zero, rather than their distance to a saline aquifer polygon node. Figures 8 and 9 show the results of the GIS analysis, plotting the cumulative number of plants and cumulative generation capacity within varying distances of each of these three sequestration opportunities. Analysis indicates that 323 (83 percent) power plants are located within 25 miles of an oil and gas sequestration opportunity – this assumes that these oil and gas reservoirs are available for bulk CO2 storage. For saline aquifers, 244 (63 percent) plants are within 25 miles. For CO2 pipelines, because of their limited build-out at this time, only 11 plants (3 percent, representing 10 GW) are with 25 miles. When combined the results show that a total of 324 (84 percent representing 282 GW) plants of the viable population is within 25 miles of a sequestration opportunity. Therefore, a 25 mile distance was used to represent a reasonable threshold for a viable transportation of CO2 within the CCM. This is more conservative than NETL’s Bituminous Baseline Final Report1, where 50 miles was used as an appropriate distance for CO2 transportation to a saline aquifer.

1

Cost and Performance Baseline for Fossil Energy Plants, DOE/NETL-2007/1281, 2007

13

388 Plants (323 GW) 388

388

388

388

387

387

373

382

382 361

382

382 342

316

244

250

374

374 271

281

300

288

323

324

349

353

350

200

Oil and Gas

211

Saline Aq Existing CO2 Pipeline All Opportunities

150

3

23

31

44

51

50

60

100

11

Cumulative Number of Plants Within Distance

400

0 10

25

50

75

100

125

150

>150

Distance to Sequestration Opportunity (miles)

Figure 8. Distance to Sequestration Opportunities—Count of Plants

323 GW (388 Plants)

323

323

323

323

322

322

314

320

320 307

320

320 293

254

249

223

244

278

282

282

250

200 199

Oil and Gas Saline Aq Existing CO2 Pipeline

150

All Opportunities

100

61

Cumulative Capacity (GW) Within Distance

296

298

300

314

314

350

49

27

22

10

2

42

50

0 10

25

50

75

100

125

150

>150

Distance to Sequestration Opportunity (miles)

Figure 9. Distance to Sequestration Opportunities—Generation Capacity With the addition of a distance to a sequestration opportunity, the viable population comprises 324 plants, which represents 37 percent of the coal-fired generation capacity of the U.S. Figure 10 shows the viable plants in relation to plants removed from the population. Figures 11 and 12 show the distribution of plants within each category of the viable population determination by count of plants and generation capacity.

14

Figure 10. Population of Coal-Fired Power Plants

15

PC Power Plants 1200

Count of Plants

1000 800 600

1088

400

647 416

200

388

324

0 Total Plants

Operating

Above 100 MW

Below 12500  btu/kwh

Within 25 miles  of Seq

Category

Figure 11. Breakdown of Viable Population by Count of Plants

PC Power Plants 500 450 Total Capacity  (GW)

400 350 300 250

497

200

331

326

150

323

282

100 50 0 Total Plants

Operating

Above 100  MW

Below 12500  btu/kwh

Within 25  miles of Seq

Category

Figure 12. Breakdown of Viable Population by Generation Capacity

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2.3

MODEL DEVELOPMENT AND ANALYSIS

The CCM was developed to merge, process and analyze the various disparate datasets. It functions by reading parameters from the EV datasets and GIS data sources for the population of plants. The model calculates the required size and cost for the various CO2 capture components using the Conesville Study to determine scaling functionality. Costs are adjusted for construction difficulty, water availability, and additional land requirements. Further detail on the derivation of specific parameters is presented below. The CCM used upon the Conesville Study, which examined the cost and physical footprint requirements of retrofitting the 463.5 MW AEP Conesville Unit 5 with amineabsorber carbon capture technology. Critical to the CCM is a GIS imagery analysis that identifies construction difficulties associated with space constraints and existing plant layout. This analysis was used to modify the estimated CAPEX to account for increased cost of engineering and construction and the cost of additional land if needed. 2.4

PHYSICAL SIZE AND COST SCALING

In a GIS, figures identifying the required equipment were scanned from the Conesville Study and georeferenced to Google imagery of the Conesville plant site. These components were then digitized and attributed as GIS polygons so they could be scaled, relocated, and rotated to accommodate the remaining plants in the sample. These components are identified in Figure 13.

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Plant 1497, AES Conesville, Coneville OH

Figure 13. Retrofit Equipment Layout for Conesville Unit 5 The Conesville Study examined four cases with varying effective CO2 absorption percentages of 90, 70, 50 and 30 percent. The CCM assumes that retrofitted plants will scrub 90 percent of the emitted CO2. Fortunately, the Conesville Study assumed use of CO2 absorption equipment with a scrubbing capability of 90 percent—the study’s various cases were achieved by limiting the amount of flue gas diverted to the CO2 absorbers—which allowed an imputed calculation of power plant size if the equipment for each of the cases was operative at 90 percent capacity. For example, scrubbing 50 percent of the CO2 from a 435.5 MW Conesville Unit 5 is the equivalent of scrubbing 90 percent of the CO2 from a 242 MW unit. In this manner, plotting the four various Conesville Unit 5 scenarios allows for imputation of component cost functions. Other components were found to vary in cost among the cases or were dependent upon the presence and effectiveness of current emissions control equipment. The CCM calculates total capital expense (CAPEX) as follows: [(Letdown Turbine Cost + CO2 Scrubber and Absorber Cost + FGD Cost + NOx Cost) * (1+Close-In Construction Difficulty Factor)] * Multiple Unit Discount + (CO2 Separation and Compression Cost + Additional Cooling Cost) * (1+Landscape Construction Difficulty Factor ) + Additional Land Cost Each of these components is discussed in detail below. 18

2.4.1

Let-Down Turbine

The cost of the Conesville Unit 5 letdown turbine in the 90-percent scenario was $9.65 million. The costs relative to this case among the various scenarios are plotted against the scenarios’ implied generation capacity in Figure 14. As shown by the equation of the resultant graph, the cost and size of the letdown turbine for a particular unit relative to Conesville Unit 5 cost and size is determined by the function F = (0.0004 * Unit Nameplate Capacity) + 0.799.

Let down turbine y = 0.0004x + 0.799 R² = 0.9979

Cost relative to Conesville 90% case

120%

100%

80%

60%

40%

20%

0% -

200

400

600

800

1,000

Original Capacity of System, MW

Figure 14. Let-Down Turbine Cost and Size Scaling 2.4.2

CO2 Compression

The cost of the Conesville Unit 5 CO2 separation and compression in the 90 percent scenario was $379.5 million. In the Conesville study, the CO2 was dried and compressed to 2,000 psig. Figure 15 plots the costs relative to this case against the various scenarios’ implied generation capacity. As shown by the equation of the resultant graph, the cost and size of CO2 separation and compression for a particular unit relative to Conesville Unit 5 cost and size is determined by the function F = (0.0017 * Unit Nameplate Capacity) + 0.2433. Estimates of CO2 transportation, storage and monitoring costs were beyond the scope of this report and were not included in the total costs.

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CO2 Compression and Separation

Cost relative to Conesville 90% case

200% y = 0.0017x + 0.2433 R² = 0.9767

180% 160% 140% 120% 100% 80% 60% 40% 20% 0% -

200

400

600

800

1,000

Original Capacity of System, MW

Figure 15. CO2 Separation and Compression Cost and Size Scaling 2.4.3

CO2 Scrubber Cost

Based upon the Conesville Study, a cost curve for CO2 scrubbers was developed (Figure 16). Costs were scaled relative to the Conesville plant cost rate. An economy of scale was assumed for larger plants, where the largest CO2-producing unit was estimated to be 70 percent as expensive based on a per-unit basis upon a linearly extrapolated cost relative to Conesville. Once these two points were established, a natural log function was fit to the data. Further, $10 million was assumed to be a minimum cost for this equipment at a unit.

20

$60 

y = 3E‐12x3 ‐ 2E‐07x2 + 0.0054x  + 3.0266 $50 

$ millions

$40 

$30 

$20 

$10 

$‐ ‐

5,000 

10,000 

15,000 

20,000 

25,000 

Tons CO2

Figure 16. CO2 Scrubber Cost and Size Scaling 2.4.4

SO2 Removal

SO2 removal is necessary for amine-absorber carbon capture technology. Accordingly, each site was assessed for requirements of sulfur removal to a level of 98 percent in terms of cost and space. For sites that have FGD that do not remove sulfur to this level, or for sites without FGD, the need for marginal FGD equipment was assessed. In addition, to bring sulfur levels to 10 ppm requirement of the CO2 scrubbers, separate sulfur “polishing” was assessed. Current state-of-the-art MEA wet scrubbing chemicals are degraded by sulfur species contained in the flue gas stream. The chemical degradation by sulfur results in additional energy and cost associated with a solvent reclamation process and make-up solvent. In order to be reduce cost, most current amine-based systems require flue gas sulfur levels below 10ppm . Therefore, additional deep sulfur scrubbing (“sulfur polishing”) from the 98% removal to