OPPORTUNITIES FOR ENERGY OPTIMIZATION IN DRINKING WATER UTILITIES

OPPORTUNITIES FOR ENERGY OPTIMIZATION IN DRINKING WATER UTILITIES • • PAULINE MACHARIA, Kenya PhD Research Fellow, Technische Universitat, Vienna Aus...
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OPPORTUNITIES FOR ENERGY OPTIMIZATION IN DRINKING WATER UTILITIES • •

PAULINE MACHARIA, Kenya PhD Research Fellow, Technische Universitat, Vienna Austria

‘ANYONE WHO CAN SOLVE THE PROBLEMS OF WATER IS WORTHY OF TWO NOBEL PRIZES; ONE FOR PEACE AND ANOTHER FOR SCIENCE’ ~~~~ JOHN F. KENNEDY

Presentation Outline • • • •

Introduction Research Design Results and synthesis Concluding remarks

Introduction • Water and energy are intricately related ; shared vulnerabilities & opportunities • The integral relationship between water and energy (W-E Nexus) is not widely understood/ insufficiently exploited through uncoordinated, semi-holistic efficiency approaches in policy formulation(“Silo mentality”). • Despite this close linkage, information on use and optimization of energy for water is scanty especially for African drinking water utilities;

Presentation Outline • Introduction Energy • Research Design for water • Results and synthesis • Concluding remarks

Source : DOE, 2006

Water for energy

Fig 1: Summary of Water –Energy Nexus

Introduction

• Energy cost accounts for up to 60% total operating cost in drinking water utilities • Documented water losses of > ⅓ of treated water before the cost is recovered -- Water loss=Energy loss • The Nexus can be exploited to quantify and optimize energy efficiency in DWU = reduced water wastage, energy cost, GHG emissions ; increased connection;

Introduction

• Kenya is "water scarce” per capita water availability 643m3/year; projected 243 m3/year by 2025 (supply/demand drivers) • Significant changes in water resources management and conservation since the implementation of the Water Act 2002; • Separates policy formulation, regulation and services provision; defines decentralized institutional framework and allows for the privatization of drinking water utilities. • Data on EE in dwu unavailable /scattered =water and energy policies, IRM programs, CC mitigation

Method overview Data

• Documentation of energy consumption for water treatment process

Drivers

• Identification of water supply and demand drivers

Scenario building

• Scenario building on energy demand as a function of shift in water supply and demand drivers

Energy optimization

• Explore practical intervention measures to optimize energy utilization in drinking water utilities

Energy management planning

Source : Natural step, 2012

Fig 2: Backcasting approach

Water supply & demand drivers

Energy consumption Vs water production Drinking water utility

Pop. Served

Nyeri

164,781 20.4 M

Kiambere 42,000 -Mwingi Thika

Total monthly water production (M3)

4.2 M

150,300 14.8 M

Energy consump tion (kWh/M3

Total monthly energy cost (Ksh)

NRW

Age of pumps

Pumping efficiency

0.7

15 M

22%

8 yrs

75%

0.9

3.5 M

40%

18 yrs

65%

0.9

9M

35%

12 yrs

65%

Energy intensities in water treatment processes (kWh/M3)

Source &

conveyance

• 0• 0.37 1,400

Treatment

0.03

• 0.03 • (100)

( 100)

Distribution

• 0.42 (1,600)

0.32 (1,200)

Major challenges facing drinking water utilities • Non-revenue water (illegal connections • Aging infrastructure • Lack of investment • Technological shifts

Intervention measures

Intervention

Energy savings/yr

Water savings/yr

Total cost savings/yr

Other benefits

Pump pressure optimization

10-18M kWh

12,000M3

5M $US

Water loss reduction

Prepaid metering, behavior change

9-12M kWh

5,000M3

2M $US

Upto 90% payment rate increment

Energy Audits

5M kWh

336,000$US

10% more supply no additional capacity

Maximizing existing pump systems efficiency, storage

70M kWh

2.5M $US with an Investment of $1.1M

88,000 new connections over the original baseline

Concluding remarks • Potential exists in saving energy for water ; energy generation at abstraction points and exploration into renewables.

• Harmonization of Energy and water policies allow for better planning and savings for energy and water • The success of any intervention measure dependent on technology; local capacity to implement; age of infrastructure

Thank you