Design and evaluation of seasonal storage hydrogen peak electricity supply system

DESIGN AND EVALUATION OF SEASONAL STORAGE

HYDROGEN PEAK ELECTRICITY SUPPLY SYSTEM

by

Isaiah Olanrewaju Oloyede

B.Eng., Electrical and Electronic Engineering (2001) Federal University of Technology, Akure

M.Eng., Electrical Engineering (2008) Cornell University, Ithaca

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SUBMITTED TO THE DEPARTMENT OF NUCLEAR SCIENCE AND ENGINEERING

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN NUCLEAR SCIENCE AND ENGINEERING

AT THE

MASSACHUSETTS INSTITUTE OF TECHNOLOGY JUNE 2011

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Department dNuclea Science and Engineering May 14, 2011

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Thesis Supervisor

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Accepted by:...

Mujid S. Kazimi TEPCO U essor of Nuclear Engineering Chair, Department Committee on Graduate Students

DESIGN AND EVALUATION OF SEASONAL STORAGE HYDROGEN PEAK ELECTRICITY SUPPLY SYSTEM

By

Isaiah Olanrewaju Oloyede

Submitted to the Department of Nuclear Science and Engineering on May 14, 2011 in Partial Fulfillment of the Requirements for the Degree of

Master of Science in Nuclear Science and Engineering

Abstract

The seasonal storage hydrogen peak electricity supply system (SSHPESS) is a gigawatt-year hydrogen storage system which stores excess electricity produced as hydrogen during off-peak periods and consumes the stored hydrogen to produce electricity during peak periods of electricity demand. This thesis investigated and produced high-level system requirements and designs for an SSHPESS.

To determine the daily, weekly, and seasonal requirements, analytical and numerical mod-els were developed for all-nuclear, all-wind, and all-solar electricity coupled to storage systems. The electricity demand characteristics were obtained using actual electricity de-mand data from power grid operators from the North-East and South-West United States (New England, New York, PJM, and California). For an all-nuclear system, it was assumed that electricity was produced at a constant rate. For the wind and solar generating systems, real wind and solar data were obtained using models of wind and solar trough electricity systems.

The analyses of the demand characteristics show that for a system containing only base-load plants (all-nuclear electricity systems) with lossless large-scale electricity storage systems, the base-load demand would increase by 50% relative to current electrical infrastructure and 93% of the electricity would be sent directly to customers. About 7% of the annual electricity production would be sent to storage at times of low electricity demand for use at times of high electricity demand. The "7% Nuclear Electricity to Storage Ratio" is applicable to all the power grids considered. Analyses done for inefficient storage systems show that about 11% of the energy produced is sent to storage. The results also show that all-nudear electricity system requires the least amount of energy storage capacity for seasonal energy storage. As an example, the California grid data is shown below assuming the H2 storage system meets hourly, daily, or weekly energy storage needs.

Table 1: California Storage Energy Requirements as Fraction of Total Energy Produced for Idealized Storage

Hourly Daily Weekly Nuclear 0.07 0.04 0.04

Wind 0.45 0.36 0.25

Solar 0.5 0.21 0.17

Thesis Supervisor: Charles W. Forsberg

Acknowledgments

"In every thing give thanks: for this is the will of God in Christ Jesus concerning you." - 1 Thessalonians 5:17-19, The Holy Bible (King James Version)

First, I would like to express my sincere gratitude to Total for their financial support and the opportunities.

I would also like to thank the donors of the Theos

J

I would like to express my appreciation to my advisors, Dr. Charles Forsberg and Professor Michael Driscoll, for providing me with the right guidance, assistance and direction. Thank you for all the recommendations and contributions to the thesis.

I would like to thank Professors Mujid Kazimi and Jacopo Buorgiorno for their assistance with funding to complete this thesis.

To my family, Toyin, Tobi (Ebenezer), Jomiloju (Hadassah), and Fayosola (Joshua), thank you for all the sacrifices you made.

To my parents, thank you for your sacrifices and love. To my siblings, Funmi, Deboye, Sola, Biola, and Lola, thank you for your constant prayers and support. To Olalekan Oloyede, Funmilola Owoade and Ms. Sade Taiwo, thank you for your support, care and love. To Patrick Taiwo, Lai Fafowora and Eloka Uzodike, thank you for your unwavering sup-port, guidance and assistance.

To Oladapo Obitayo, words cannot express how valuable you are to me and my family. Thank you for being more than a friend.

To Susan Malley, thank you for your help in recovering the files I lost when I had issues with my computer.

To Professor Bingham K. Cady, thank you. To Roza Tesfaye, thank you and promises kept!

I would also like to thank my friends and colleagues who helped me in one way or another to grasp the concepts written down in this thesis. My memory may fail me if I attempt to recall all your names. Thank you very much.

Contents

1.1 Background -The Electric Power System 1.2 Problem Definition ...

1.3 Motivations ...

1.3.1 Responsive Energy Management .

1.3.2 Renewables Portfolio Management 1.3.3 Contingency Reserves ... 1.3.4 Enhanced Asset Management .. . 1.3.5 Transmission Enhancement .... 1.3.6 Economic Value ... 1.3.7 Environmental Impacts ... 1.4 Thesis Objectives ... 1.5 Scope of Work ... 1.6 Thesis Organization ... 2 Literature Review 2.1 Introduction . . . . 2.2 Storage Requirements . . . . 2.3 Electricity Storage Systems . . . .

2.3.1 Water: Pumped Hydro Energy Storage (PHES) . . . .

2.3.2 Compressed Air: Compressed Air Energy Storage (CAES) . .

2.3.3 Heat: Thermal Energy Storage (TES) ... 2.3.4 Other Storage Media: Storage Systems ... 2.4 Hydrogen as an Energy Storage Medium ...

2.4.1 Seasonal Storage Hydrogen Peak Electricity Supply System

PESS) Design ...

2.4.2 Hydrogen Production and Storage ... 2.4.3 Oxygen Production and Storage ...

3 5 11 16 19 23 23 26 27 28 30 31 32 32 32 32 33 34 34 37 37 37 38 38 39 40 40 42 43 43 58

(SSH-2.4.4 Hydrogen -Oxygen Electricity Production . . . . 64

2.5 Sum m ary ... . 66

3 Analysis and Results of Idealized Electricity Demand and Storage Requirements 67 3.1 Introduction ... . 67

3.2 Analysis of Electricity Demand and Storage Requirements ... 67

3.2.1 Demand Curves ... 68

3.2.2 Demand Characteristics ... 72

3.2.3 Summary of Demand Characteristics ... 92

3.2.4 Power Storage Curves ... . 92

3.2.5 Energy Storage Capacity Curves ... 94

3.2.6 Storage Characteristics ... 94

3.3 Analysis of Lossless Nuclear Production and Storage Requirements ... .101

3.3.1 Nuclear Production Curves ... 101

3.3.2 Nuclear Power Storage Curves ... 102

3.3.3 Nuclear Energy Storage Capacity Curves ... 107

3.3.4 Nuclear Storage Characteristics ... 111

3.3.5 Summary of Nuclear Storage Characteristics ... 122

3.4 Analysis of Lossless Wind Production and Storage Requirements . . . 123

3.4.1 Wind Production Curves ... 124

3.4.2 Wind Power Storage Curves ... 127

3.4.3 Wind Energy Storage Capacity Curves ... 131

3.4.4 Wind Storage Characteristics ... 136

3.4.5 Summary of Wind Storage Characteristics ... 145

3.5 Analysis of Lossless Solar Production and Storage Requirements ... 147

3.5.1 Solar Production Curves ... 147

3.5.2 Solar Power Storage Curves ... 148

3.5.3 Solar Energy Storage Capacity Curves ... 153

3.5.4 Solar Storage Characteristics ... 157

3.5.5 Summary of Solar Storage Characteristics ... 164

3.6 Analysis of Lossless Generation-Mix and Storage Requirements ... .166

3.6.1 Storage Requirements for Nuclear - Wind Power Generation Mix . . 167

3.6.2 Storage Requirements for Nuclear -Solar Power Generation Mix . . 169

3.6.3 Storage Requirements for Wind -Solar Power Generation Mix . ... 171

3.6.4 Storage Requirements for Nuclear -Wind -Solar Power Generation M ix. . . . .. ... . . ... .. . . . .. 172

3.7 Summary ... 174

4 Analysis and Results of Inefficient Electricity Demand and Storage Requirements175 4.1 Introduction ... 175

4.2 Definition of Efficiency-Related Terms ... 175

4.2.1 System Efficiencies ... 175

4.2.2 Reservoir Sizing Ratio ... 178

4.2.3 Inefficient Power Storage Curves ... 179

4.2.4 Power Production for Inefficient Storage Systems ... 180

4.2.5 Inefficient Energy Storage Capacity Curves ... 181

4.2.7 Ratio of Full Storage Capacity (FSC) to Equilibrium Energy Produced (EEP)...

4.3 Analysis of Inefficient Nuclear Production and Storage Requirements .... 4.3.1 Nuclear Production Curves . . . .

4.3.2 Nuclear Power Storage Curves . . . . 4.3.3 Nuclear Energy Storage Capacity Curves . . 4.3.4 Nuclear Storage Characteristics ...

4.3.5 Summary of Nuclear Storage Characteristics 4.4 Analysis of Inefficient Wind Production and Storage

4.4.1 Wind Production Curves . . . . 4.4.2 Wind Power Storage Curves . . . .

4.4.3 Wind Energy Storage Capacity Curves . . . 4.4.4 Wind Storage Characteristics . . . . 4.4.5 Summary of Wind Storage Characteristics . 4.5 Analysis of Inefficient Solar Production and Storage

4.5.1 Solar Production Curves . . . . 4.5.2 Solar Power Storage Curves . . . . 4.5.3 Solar Energy Storage Capacity Curves . . . . 4.5.4 Solar Storage Characteristics . . . . 4.5.5 Summary of Solar Storage Characteristics . . 4.6 Summary ...

5 Design of the Seasonal Storage Systems 5.1 Introduction ...

5.2 Underground Storage Volumetric Measures . 5.3 Hydrogen and Oxygen Storage Requirements 5.4 Hydrogen and Oxygen Storage Design . . . . 5.5 Challenges with Underground Hydrogen and 6 System Requirements

6.1 Introduction ...

6.2 System Objectives and Constraints . . . . 6.2.1 SSHPESS Mission Statement . . . . . 6.2.2 SSHPESS Mission Objectives . . . . . 6.2.3 SSHPESS Operational Objectives . . . 6.2.4 SSHPESS Mission Success Criteria . . 6.2.5 Design Drivers ...

6.3 Technical Requirements . . . . 6.3.1 System Functional Requirements ... 6.3.2 System Performance Requirements. .

Oxyg 187 189 ... .... 189 Requirements Requirements . Storage . . . 192 198 203 221 223 223 225 234 236 257 259 259 267 268 275 290 291 293 293 293 294 296 297 299 299 299 299 299 300 301 301 301 302 302 303 303 307 307 307 308 6.3.3 System Interface Requirements

6.4 Design Options for the Peak Hydrogen Electri

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

city Supply System .

7 Evaluation of Design Options

7.1 Introduction ...

7.2 Technology Readiness Level Assessment ...

7.3 Economic Analysis and Valuation ...

8 Summary, Conclusions and Recommendations 311 8.1 Summary of Findings ... 311 8.2 Recommendations for Further Work ... 313

List of Figures

1-1 Electric Power System Configuration and Structure . . . . 24

1-2 Hydrogen Energy Storage Concept . . . . 27

1-3 Capability Comparison of Proposed Hydrogen Storage System to Existing Electricity Storage Technologies. . . . . 28

2-1 Theoretical Energy Consumption for Hydrogen Production from Different Feedstocks ... 46

2-2 Maximum Theoretical Yield of Hydrogen Produced by Steam Reforming (Gasification) of Different Feedstocks . . . . 47

2-3 General Classification of Hydrocarbon-to-Hydrogen Processes ... . 48

3-1 A Sinusoidal Demand Curve with Period, T = 1 year ... 69

3-2 A Sinusoidal Demand Curve with Period, T = 1/2 year ... 69

3-3 Hourly Demand Curves for Selected Grid Systems, 2008 ... 70

3-4 Daily Demand Curves for Selected Grid Systems, 2008 ... 71

3-5 Weekly Demand Curves for Selected Grid Systems, 2008 ... 72

3-6 A Sinusoidal Demand Curve with Period = 1/2 year showing Demand Char-acteristics .. ... .. . ... .. .. ... .. ... ... . 73

3-7 Projected Nuclear Production Curve for Idealized Sinusoidal Systems ... 102

3-8 Projected Nuclear Production Curves for Selected Grid Systems ... .103

3-9 Power Storage Curve for Idealized Nuclear Production Curve, Period = 1 year104 3-10 Power Storage Curve for Idealized Nuclear Production Curve, Period = 1/2 year . . . .. . . . 104

3-11 Hourly Nuclear Power Curves for Selected Grid Systems, 2008 ... 105

3-12 Daily Nuclear Power Curves for Selected Grid Systems, 2008 ... .106

3-13 Weekly Nuclear Power Curves for Selected Grid Systems, 2008 ... 106

3-14 Energy Storage Curve for Idealized Nuclear Production Curve, Period = 1 year.. . . . .. .. .. . .. . .. . . . 107

3-15 Energy Storage Curve for Idealized Nuclear Production Curve, Period = 1/2 year . . . .. . . . 108

3-16 Hourly Nuclear Energy Curves for Selected Grid Systems, 2008 ... .109

3-17 Daily Nuclear Energy Curves for Selected Grid Systems, 2008 ... .110

3-18 Weekly Nuclear Power Curves for Selected Grid Systems, 2008 ... 110

3-19 A Sinusoidal Wind Production Curve ... 125

3-20 Hourly Wind Production Curves for Selected Grids, 2005 ... .126

3-21 Daily Wind Production Curves for Selected Grids, 2005 ... 126

3-22 Weekly Wind Production Curves for Selected Grids, 2005 ... .127 3-23 Wind Power Storage Curve for Idealized Demand Curve, Period = 1 year . 128

3-24 Wind Power Storage Curve for Idealized Demand Curve, Period = 1/2 year 129

3-25 Hourly Wind Power Storage Curves for Selected Grids, 2005 ... .130

3-26 Daily Wind Power Storage Curves for Selected Grids, 2005 ... .130

3-27 Weekly Wind Power Storage Curves for Selected Grids, 2005 ... .131

3-28 Wind Energy Storage Curve for Idealized Demand Curve, Period = 1 year . 132 3-29 Wind Energy Storage Curve for Idealized Demand Curve, Period = 1/2 year 133 3-30 Hourly Wind Energy Storage Curves for Selected Grids, 2005 ... 134

3-31 Daily Wind Energy Storage Curves for Selected Grids, 2005 ... .135

3-32 Weekly Wind Energy Storage Curves for Selected Grids, 2005 ... 135

3-33 A Sinusoidal Solar Production Curve ... 148

3-34 CAISO Hourly Solar Production Curves, 2005 -2007 ... 149

3-35 CAISO Daily Solar Production Curves, 2005 -2007 ... 150

3-36 CAISO Weekly Solar Production Curves, 2006 ... 151

3-37 Solar Power Storage Curve for Idealized Demand Curve, Period = 1 year. . 152 3-38 CAISO Hourly Solar Power Storage Curves, 2005 -2007 ... .154

3-39 CAISO Daily Solar Power Storage Curves, 2005 - 2007 ... 155

3-40 CAISO Weekly Solar Power Storage Curves, 2006 ... 156

3-41 Solar Energy Storage Curve for Idealized Demand Curve, Period = 1 year . 157 3-42 CAISO Hourly Solar Energy Storage Curves, 2005 - 2007 ... 158

3-43 CAISO Daily Solar Energy Storage Curves, 2005 - 2007 ... 159

3-44 CAISO Weekly Solar Energy Storage Curves, 2006 ... 160

3-45 TESR/TEP Ratio for Nuclear-Wind Power Generation Mix ... 168

3-46 CAISO FSC/TEP Ratio for Nuclear-Wind Power Generation Mix ... .169

3-47 CAISO TESR/TEP Ratio for Nuclear-Solar Power Generation Mix ... 170

3-48 CAISO FSC/TEP Ratio for Nuclear-Solar Power Generation Mix ... .170

3-49 CAISO TESR/TEP Ratio for Wind-Solar Power Generation Mix ... .171

3-50 CAISO FSC/TEP Ratio for Wind-Solar Power Generation Mix ... .172

3-51 CAISO TESR/TEP Ratio for Nuclear-Wind-Solar Power Generation Mix . . 173

3-52 CAISO FSC/TEP Ratio for Nuclear-Wind-Solar Power Generation Mix ... 173

4-1 Simple Model Showing Relationshipbetween Storage and Conversion Losses Only (No Leakage or Regeneration Losses) ... 176

4-2 Simple Model Showing Storage and Losses ... 176

4-3 Idealized (dotted) and Non-Idealized (solid) Nuclear Production Curves . . 191

4-4 Projected Nuclear Production Curves for Selected Grid Systems ... .192

4-5 Non-Idealized Power Storage Curve for Nuclear Electricity Production, Pe-riod = 1 Year ... 193

4-6 Non-Idealized Power Storage Curve for Nuclear Electricity Production, Pe-riod = 1/2 Year ... 193

4-7 Hourly Nuclear Power Storage Curves for Selected Grids, 2008 - Typical Storage Case (52% Efficiency) ... 195

4-8 Daily Nuclear Power Storage Curves for Selected Grids, 2008 -Typical Stor-age Case (52% Efficiency) ... 195

4-9 Weekly Nuclear Power Storage Curves for Selected Grids, 2008 - Typical Storage Case (52% Efficiency) ... 196

4-10 Hourly Nuclear Power Storage Curves for Selected Grids, 2008 - Advanced Storage Case (71% Efficiency) ... 196

4-11 Daily Nuclear Power Storage Curves for Selected Grids, 2008 -Advanced Storage Case (71% Efficiency) . . . 197 4-12 Weekly Nuclear Power Storage Curves for Selected Grids, 2008 -Advanced

Storage Case (71% Efficiency) . . . 197 4-13 Non-Idealized Energy Storage Curve for Nuclear Electricity Production,

Pe-riod = 1 year ... 198 4-14 Non-Idealized Energy Storage Curve for Nuclear Electricity Production,

Pe-riod = 1/2 year ... 199 4-15 Hourly Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Typical Storage Case (52% Efficiency) . . . 200 4-16 Daily Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Typical Storage Case (52% Efficiency) . . . 201 4-17 Weekly Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Typical Storage Case (52% Efficiency) . . . 201 4-18 Hourly Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Advanced Storage Case (71% Efficiency) . . . 202 4-19 Daily Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Advanced Storage Case (71% Efficiency) ... 202 420 Weekly Nuclear Energy Storage Capacity Curves for Selected Grids, 2008

-Advanced Storage Case (71% Efficiency) ... 203 4-21 Idealized (dotted) and Non-Idealized (solid) Wind Production Curves,

Pe-riod T = 1 year ... 224 4-22 Idealized (dotted) and Non-Idealized (solid) Wind Production Curves,

Pe-riod T = 1/2 year ... 224 4-23 Hourly Wind Production Curves for Selected Grids, 2005 - Typical Storage

Case (52% Efficiency) ... 226 4-24 Daily Wind Production Curves for Selected Grids, 2005 - Typical Storage

Case (52% Efficiency) ... 226 4-25 Weekly Wind Production Curves for Selected Grids, 2005 -Typical Storage

Case (52% Efficiency) ... 227 4-26 Hourly Wind Production Curves for Selected Grids, 2005- Advanced Storage

Case (71% Efficiency) ... 227 4-27 Daily Wind Production Curves for Selected Grids, 2005 - Advanced Storage

Case (71% Efficiency) ... 228 4-28 Weeklv Wind Production Curves for Selected Grids, 2005- Advanced Storage

Case (71% Efficiency) ... 228

4-29 Non-Idealized Wind Power Storage Curve for Idealized Demand Curve, Period = 1 year ... 229 4-30 Non-Idealized Wind Power Storage Curve for Idealized Demand Curve,

Period = 1/2 year ... 229 4-31 Hourly Wind Power Storage Curves for Selected Grids, 2008- Typical Storage

Case (52% Efficiency) ... 231 4-32 Daily Wind Power Storage Curves for Selected Grids, 2008 -Typical Storage

Case (52% Efficiency) ... 231 4-33 Weekly Wind Power Storage Curves for Selected Grids, 2008-Typical Storage

Case (52% Efficiency) ... 232 4-34 Hourly Wind Power Storage Curves for Selected Grids, 2008 - Advanced

4-35 Daily Wind Power Storage Curves for Selected Grids, 2008 - Advanced Storage Case (71% Efficiency) ... 233 4-36 Weekly Wind Power Storage Curves for Selected Grids, 2008 - Advanced

Storage Case (71% Efficiency) ... 233 4-37 Non-Idealized Wind Energy Storage Curve for Demand Curve, Period = 1

year . . . .. . . . 234 4-38 Non-Idealized Wind Energy Storage Curve for Demand Curve, Period = 1/2

year . . . 235 4-39 Hourly Wind Energy Storage Capacity Curves for Selected Grids, 2008

-Typical Storage Case (52% Efficiency) ... 237 4-40 Daily Wind Energy Storage Capacity Curves for Selected Grids, 2008 -

Typ-ical Storage Case (52% Efficiency) ... 237 4-41 Weekly Wind Energy Storage Capacity Curves for Selected Grids, 2008

-Typical Storage Case (52% Efficiency) ... 238 4-42 Hourly Wind Energy Storage Capacity Curves for Selected Grids, 2008

-Advanced Storage Case (71% Efficiency) ... 238 4-43 Daily Wind Energy Storage Capacity Curves for Selected Grids, 2008 -

Ad-vanced Storage Case (71% Efficiency) ... 239 4-44 Weekly Wind Energy Storage Capacity Curves for Selected Grids, 2008

-Advanced Storage Case (71% Efficiency) ... 239 4-45 Idealized (dotted) and Non-Idealized (solid) Solar Production Curves,

Pe-riod T = 1 year ... 260

4-46 Hourly Solar Production Curves for Selected Grids, 2005 - 2007 - Typical

Storage Case (52% Efficiency) ... 261

4-47 Daily Solar Production Curves for Selected Grids, 2005 - 2007 - Typical

Storage Case (52% Efficiency) ... 262

4-48 Weekly Solar Production Curves for Selected Grids, 2005 - 2007 - Typical

Storage Case (52% Efficiency) ... 263 4-49 Hourly Solar Production Curves for Selected Grids, 2005 - 2007 - Advanced

Storage Case (71% Efficiency) ... 264

4-50 Daily Solar Production Curves for Selected Grids, 2005 - 2007 - Advanced

Storage Case (71% Efficiency) ... 265 4-51 Weekly Solar Production Curves for Selected Grids, 2005 - 2007 - Advanced

Storage Case (71% Efficiency) ... 266 4-52 Non-Idealized Solar Power Storage Curve for Idealized Demand Curve,

Period = 1 year ... 267 4-53 Hourly Solar Power Curves for Selected Grids, 2005 -2007 -Typical Storage

Case (52% Efficiency) ... 269

4-54 Daily Solar Power Curves for Selected Grids, 2005 - 2007 -Typical Storage

Case (52% Efficiency) ... 270 4-55 Weekly Solar Power Curves for Selected Grids, 2005 -2007- Typical Storage

Case (52% Efficiency) ... 271

4-56 Hourly Solar Power Curves for Selected Grids, 2005 - 2007 - Advanced

Storage Case (71% Efficiency) ... 272 4-57 Daily Solar Power Curves for Selected Grids, 2005 -2007 -Advanced Storage

Case (71% Efficiency) ... 273

4-58 Weekly Solar Power Curves for Selected Grids, 2005 - 2007 - Advanced

4-59 Non-Idealized Solar Energy Storage Curve for Idealized Demand Curve,

Period = 1 year ... 275

4-60 Hourly Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Typical Storage Case (52% Efficiency) . . . 276

4-61 Daily Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Typical Storage Case (52% Efficiency) . . . 277

4-62 Weekly Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Typical Storage Case (52% Efficiency) . . . 278

4-63 Hourly Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Advanced Storage Case (71% Efficiency) . . . 279

4-64 Daily Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Advanced Storage Case (71% Efficiency) . . . 280

4-65 Weekly Solar Energy Storage Capacity Curves for Selected Grids, 2005 -2007 -Advanced Storage Case (71% Efficiency) . . . 281

5-1 Schematic Representation of Underground Hydrogen Gas Storage. . . . 297

6-1 SSHPESS High-Level Functional Architecture . . . 304

6-2 SSHPESS High-Level Physical Architecture Options ... 305

List of Tables

1.1 Definitions and Categories of Electric Power System Applications of Energy Storage ...

2.1 Properties of Hydrogen ... 2.2 Properties of Oxygen ...

3.1 Original Base Loads for Four Grid Systems . . . . 3.2 Peak Demands for Four Grid Systems ...

3.3 Optimal Base Loads for Four Grid Systems ... 3.4 Amplitudes for Four Grid Systems ...

3.5 Seasonal Power Variation for Four Grid Systems ...

3.6 Seasonal Power Variation to Amplitude Ratios for Four Grid Systems .... 3.7 Peak Demand to Original Base Load Ratios for Four Grid Systems ... 3.8 Amplitude to Original Base Load Ratios for Four Grid Systems ... 3.9 Peak Reserve Power for Four Grid Systems ...

3.10 Peak Reserve Power to Original Base Load Ratios for Four Grid Systems . . 3.11 Peak Reserve Power to Optimal Base Load Ratios for Four Grid Systems . . 3.12 Demand Characteristics for Four Grid Systems ...

3.13 Total Energy Produced for Four Grid Systems ...

3.14 Nuclear Total Energy Storage Requirements for Four Grid Systems ... 3.15 3.16 3.17 3.18 3.19 3.20 3.21 3.22 3.23 3.24 3.25 3.26 3.27 3.28 3.29 3.30 3.31 3.32

Nuclear Full Storage Capacity for Four Grid Systems ... Nuclear Time to Full Capacity Ratios for Four Grid Systems . Nuclear TESR / APOB Ratios for Four Grid Systems ... Nuclear TESR/TEP Ratios for Four Grid Systems ... Nuclear FSC/TEP Ratios for Four Grid Systems ... Nuclear FSC/TESR Ratios for Four Grid Systems ... Nuclear Storage Characteristics for Four Grid Systems ....

Reference Wind Farms for Four Grid Systems ...

Coordinates for Reference Wind Farms for Four Grid Systems NREL Wind Site Information for Four Grid Systems ...

29 45 60 74 75 77 79 80 82 83 85 88 89 91 93 98 112 ... 114 ... 116 .... .... 117 ... 118 ... 119 ... 121 ... 122 ... 123 ... 123 ... 124 Wind Total Energy Storage Requirements, (TESR).W, for Four Grid Systems Wind Full Storage Capacity, (FSC).,, for Four Grid Systems ...

Wind Time to Full Capacity, (TTFC),, for Four Grid Systems ... Wind TESR/APOB Ratios, (TESR/APOB),,,d, for Four Grid Systems ... Wind TESR/TEP Ratios, (TESR/TEP).,, for Four Grid Systems ... Wind FSC/TEP Ratios, (FSC/TEP).W, for Four Grid Systems ... Wind FSC/TESR Ratios, (FSC/TESR),,d, for Four Grid Systems ... Wind Storage Characteristics for Four Grid Systems ...

137 139 140 141 142 143 145 146

3.33 Detailed Solar Storage Characteristics for California Grid System . . . 161

3.34 Summary Solar Storage Characteristics for California Grid System . . . 165

4.1 Efficiency Values . . . 189

4.2 Total Energy Storage Requirement for Four Grid Systems . . . 206

4.3 Full Storage Capacity for Four Grid Systems . . . 208

4.4 Tune to Full Capacity for Four Grid Systems ... 210

4.5 Nuclear TESR / APOB for Four Grid Systems . . . 212

4.6 Nuclear TESR / EEP for Four Grid Systems ... 214

4.7 Nuclear FSC / EEP for Four Grid Systems ... 216

4.8 Nuclear FSC / TESR for Four Grid Systems ... 218

4.9 Nuclear Total Energy Consumed (TEC) / Equilibrium Energy Produced (EEP) for Four Grid Systems ... 220

4.10 Summary of Non-Idealized Nuclear Storage Characteristics for Four Grid Systems ... 222

4.11 Wind TESR for Four Grid Systems ... 242

4.12 Wind FSC for Four Grid Systems ... 244

4.13 Wind TTFC for Four Grid Systems ... 246

4.14 Wind TESR / APOB for Four Grid Systems ... 248

4.15 Wind TESR / EEP for Four Grid Systems ... 250

4.16 Wind FSC / EEP for Four Grid Systems ... 252

4.17 Wind FSC / TESR for Four Grid Systems ... 254

4.18 Wind Total Energy Consumed (TEC) / Equilibrium Energy Produced (EEP) for Four Grid Systems ... 256

4.19 Summary of Non-Idealized Wind Storage Characteristics for Four Grid Sys-tem s. . .. . . . ... .. . . . .. .. ... . . .. . .. . . .. . . . 258

4.20 Solar Total Energy Storage Requirements for California Grid System .... 283

4.21 Solar Full Storage Capacity for California Grid System ... 284

4.22 Solar Tune To Full Capacity for California Grid System ... 284

4.23 Solar TESR/APOB for California Grid System ... 285

4.24 Solar TESR/EEP for California Grid System ... 286

4.25 Solar FSC/EEP for California Grid System ... 287

4.26 Solar FSC/TESR for California Grid System ... 288

4.27 Solar Total Energy Consumed (TEC) / Equilibrium Energy Produced (EEP) for California Grid System ... 289

4.28 Summary of Non-Idealized Solar Storage Characteristics for California Grid System .. . ... .. ... ... .. . .... 290

5.1 Number of Storage Sites Per Selected Grid ... 296

7.1 Technology Readiness Levels ... 308

Nomenclature

Abbreviations

APOB Annual production from original base load plant operation(s) EEP Equilibrium Energy Produced

FSC Full storage capacity TEP Total energy produced

TESR Total energy storage requirement TTFC Tune to full capacity

ISO Independent System Operator ISONE ISO New England

NYISO New York ISO PJM PJM Interconnection CAISO California ISO Symbols

a Amplitude to original base load ratio

P

r1 Efficiency

y Peak reserve power to optimal base load ratio

T Tune in fraction of a year

cp Peak reserve power to original base load ratio

A Amplitude

B0 Original Base Load

E(T) Energy storage as a function of time, T E(m) Set of energy storage data for year, m K Seasonal power variation to amplitude ratio

[MWhe] [MWhe] [MWhe] [MWhe] [MWhe] [Fraction of a Year] [MWe] [MWe] [MWe] [MWhe] [MWhe]

I Electricity demand data set element [MWe]

L(T) Electricity demand or load as a function of time, T [MWe]

L(m) Set of electricity demand for year, m [MWe]

M Total number of years, [Years]

m Year

P Peak Demand [MWe]

PO Optimal Base Load [MWe]

Pe(T) Electric power production as a function of time, T [MWe]

pe Electricity production data set element [MWe]

Pe(m) Set of electric power production data for year, m [MWe]

Pr Peak reserve power [MWe]

S('r) Power storage as a function of time, r [MWe]

S(m) Set of power storage data for year, m [MWe]

T(m) Number of hours, days, or weeks in the year, m

Z Losses [MWhe]

x Nuclear fraction of total energy produced y Wind fraction of total energy produced z Solar fraction of total energy produced

Subscripts

ip Reservoir Sizing Ratio

Ir Time in hours, days, or weeks ave Average

C Conversion (Electricity - to - H2)

G Grid Operator

R Regeneration (H2 - to - Electricity)

S Storage (Hydrogen)

s Idealized sinusoidal demand model Z Inefficient system

src Electricity generation source nuc Nuclear power plant(s) wnd Wind power plant(s) sol Solar power plant(s)

mix Mix of electricity generation from nuclear, wind, and solar power plants Superscripts

j

Chapter 1

Introduction

This chapter provides background information on the electric power system and the ben-efits of electricity storage technologies. It provides the motivations for investigating the design and evaluation of a seasonal storage system that uses hydrogen for peak electricity power production. It also elucidates the proposed objectives for the research and delineates the scope of the research work and the thesis organization.

1.1

Background

-

The

Electric Power System

Electricity, because it is clean, versatile and controllable [1], has been adapted for various domestic, commercial and industrial applications. How much electricity is produced and consumed in any country is also an indication of its economic development [1]. As adaptable as electricity is, and as crucial as it is to economic and social development, it however cannot be stored. To store electricity, it has to be converted into other forms of energy, hence there is therefore the need for electric generation to always instantaneously match electric consumption.

The electric power system can be broadly grouped into four complex components: gen-erating station or power plant, high voltage (HV) transmission network, otherwise called power (or electric) grid, distribution network and load. Electrical power produced at the generating stations is delivered to the consumers' loads through the transmission and dis-tribution networks. Figure 1-1 shows the four complex components of the electric power systems.

Electricity is produced by means of a power generator, which converts other forms of energy into electric energy. These forms of energy can be thermal energy from the combustion of fossil fuels or biomass, nuclear fission, solar or geothermal resources, mechanical energy from wind, water currents or falling water, or solar energy from sunlight. A generation (or power) station (or plant) consists of generators and the ancillary equipment required for the operation and control of the generators [2].

Based on dispatchability, power plants can alternatively be classified as dispatchable (generation-on-demand) power plants and non-dispatchable power plants [3]. Accord-ing to the Independent Power Producers of New York (IPPNY), "dispatchability is the

Interconnections

Meclum

consumers Snai

consmers

Figure 1-1: Electric Power System Configuration and Structure [1]

ability of a generating unit to increase or decrease generation, or to be brought on line or shut down at the request of a utility's system operator." [4]. Therefore, dispatchable or generation-on-demand power plants are those generating units whose power outputs can be increased or decreased, or brought on line or shut down at the request of a utility's system operator. Outputs from dispatchable power plants can be scaled back on request

by the system operator if there is an anticipation of excess production on the grid. The

utility's system operator may also request that the output of such plants be increased to ac-commodate an increase in electricity demand. On the other hand, non-dispatchable power plants are those generating units whose power outputs cannot be increased or decreased, or brought on line or shut down at the request of a utility's system operator. The outputs from a non-dispatchable power plant is either consumed as soon as it is produced, stored if there is a large enough suitable storage device, or dumped if there is an excess production beyond what the storage system can hold or the power grid can consumed. Power plants whose primary energy output is heat are often non-dispatchable. Examples of dispatch-able power plants include fossil-fueled power plants, and conventional hydropower plants. Examples of non-dispatchable power plants include nuclear, wind, solar, geothermal, and biomass power plants. Large-scale energy storage systems enable the dispatchability of power from non-dispatchable power plants.

Grid operators dispatch power plants based on minimizing costs within the constraints of reliably meeting the total electricity demand and legal mandates. Power plants with high capital costs but low operating costs (nuclear, wind, solar, etc.) are first put on line. Power plants with low capital costs but high operating costs, such as natural-gas-fired plants, are used to match electricity production with demand. The lowest cost systems typically

have multiple types of power plants because of the variable electricity demand and the characteristics of different types of electricity generators [3].

" Nuclear. Nuclear power is a capital-intensive low-operating-cost technology that provides low-cost base-load electricity. However, if all electricity was produced from nuclear reactors, the reactors producing peak electricity would operate at partial load at times of low electricity demand. The electricity costs from these peaking power plants would be high because less electricity would be produced to pay off the initial capital cost of the plant.

" Natural gas. The capital cost of natural gas plants is low but the operating costs are high because of the cost of the fuel. These have become the preferred option in the United States to meet peak electricity demands. The electricity is expensive but less expensive than would be production of electricity from capital intensive plants

(nuclear, wind, and solar) operating at only part of their capacity.

" Wind and solar. The economic structure of wind and solar are similar to nuclear

- high capital costs and low operating costs. Economics strongly depends upon operating the plants at their full capacity but output often does not match demand, such as wind at night in the spring and fall at times of low electricity demand. The economics strongly depend upon the generating source that provides backup power when the wind does not blow or the sun does not shine.

Cost effective electricity storage systems would enable capital-intensive low-operating cost generating technologies (nuclear, wind, and solar) to replace natural gas for production of intermediate and peak electricity. There are large economic incentives for alternatives to natural gas for peak electricity production because of (1) uncertainties in future natural gas prices and (2) concerns about climate change that may ultimately limit the use of fossil fuels.

The transmission network or grid enables the transmission of bulk power produced at the generating plants to the distribution networks near residential, commercial or industrial areas [2]. The transmission lines are fully interconnected in a mesh-like structure to provide for alternate routes for electric power transmission in case of the failure of any generator or transmission line, to ensure dynamic equilibrium between production and consumption of electric power, and to maintain the synchronous operation of the electric power system Ill.

In order to minimize transmission losses, transmission lines are operated at high voltages. The transmission lines feed into substations, which are "the interconnection buses for the transmission lines, the transformation nodes that feed the distribution networks that reach consumers, and the centers where system measurement, protection, interruption, and dispatch equipment are sited" [1]. Thermal constraints on a transmission line limit the amount of power that can be transferred on that line to other parts of the grid. The thermal constraint exists because transmission lines heat up due to the flow of electric currents through them. Overheating causes transmission lines to expand and lengthen, thereby shortening their distances to the ground, and increasing the risk of unsafe operations [1].

The distribution network is made up of distribution lines, called feeders. The feeders re-ceive power from the substations and deliver it to the residential, commercial or industrial

areas where it is needed [2]. A feeder network is made by an interconnection of feeders such that there is always more than one path between any two points in the feeder net-work [5]. The distribution netnet-work provides connection using step-down transformers for consumers at the voltage level best suited for their scale of consumption [1]. Some form of generation for local consumption, called distributed generation, is produced and transmitted for consumption on the distribution network.

Consumer demands are also referred to as loads. Consumer demands are energy consumed by residential, industrial, and commercial users. These loads vary hourly, daily, weekly, and seasonally [6]. Load profiles, also known as load curves, represent graphically how much power is consumed as a function of time [1]. The pattern exhibited by a load curve is strongly influenced by the behavior of the consumer groups and the climatic characteristics where the consumer groups are located [7].

Because of the dynamic nature of load, the generation must be flexible enough to match the variation in the load. Since there is no device for bulk storage of electrical energy, except by converting the electrical energy to some other forms of energy, the electrical power produced by generating stations must match instantaneously the varying demands of the load and the concomitant transmission losses [6]. The demand and transmission losses

must be met with power generated at the lowest and least variable cost [1].

1.2 Problem Definition

A system that uses hydrogen for peak electricity demand has been proposed [8]. The pro-posed system uses high-temperature electrolysis during periods of low electricity demand to produce hydrogen and oxygen, which are then stored for subsequent use during periods of peak electricity demand. The stored hydrogen and oxygen can be used to produce elec-tricity by either operating the high-temperature electrolysis system as a fuel cell or running the hydrogen and oxygen through an oxygen-hydrogen steam turbine.

The concept for the proposed hydrogen energy storage system is illustrated in Figure 1-2. Electricity produced from CO2 emission-free power plants (nuclear, wind, and solar) is

supplied to the power grid. During period of low electricity demands, electricity from the power grid is sent to the electricity-to-hydrogen conversion system (low-temperature electrolyzer (LTE) or high-temperature electrolyzer (HTE)) to produce hydrogen. Hydro-gen produced is stored in the hydroHydro-gen storage system (Depleted natural gas reservoir, naturally-occurring aquifers, or mined salt caverns). During peak periods, hydrogen is withdrawn from the storage system and sent through the hydrogen-to-electricity conver-sion system (Hydrogen gas turbine, fuel cell, or oxy-hydrogen steam turbine) to generate electricity, which is then transmitted via the transmission and distribution network to customers.

This investigation aims to produce a set of detailed system requirements and system architecture (both functional and physical architecture) for the seasonal storage hydrogen peak electricity supply system. The focus will be on designing a system that will provide electricity for seasonal load variations. Pumped hydro storage and compressed air energy systems, the existing non-fossil methods currently used for supplying electrical power for peak electricity demand are suitable mainly for variable daily demand [8]. The seasonal

Nuclear Wind Solar Power Power Power

Plants Plants Plants _{Hydrogen Storage} System

Electricity-to-Hydrogen Hydrogen-to-Electricity

Conversion System Conversion System

Transmission and Distribution Network Interconnections

Consumers

Figure 1-2: Hydrogen Energy Storage Concept

storage hydrogen peak electricity supply system will provide for daily, weekly and seasonal variations.

The proposed hydrogen storage system will introduce a new storage capability into the energy storage domain -the ability to supply energy for a very long time spanning weeks, months and even up to a year as shown in Figure 1-31. The concept of seasonal storage is not novel. Seasonal storage of natural gas is a common practice in the natural gas industry. Natural gas stored for seasonal demand requirements typically has a turn-over rate of a year; natural gas is injected into storage during non-heating season (summer) and withdrawn during the heating season (winter) [9]. The United States' storage capacity for 'working gas' ("the volume of natural gas in the storage reservoir that can be extracted during the normal operation of the storage facility" [9]) is estimated to be about 4.2 Trillion standard cubic feet (Tscf) [10, 11], which is equivalent to about 144 GWyrth. In the year

2008, the total number of active fields in the United States was 401 [10]. Therefore, on the

average, each active field stores about 10,500 million standard cubic feet (MMscf), which is equivalent to about 0.361 GWyrth. Since such an amount of natural gas storage is feasible in the natural gas industry, such storage of hydrogen is feasible if existing or new natural gas storage systems are adapted to the storage of hydrogen.

1.3

Motivations

The four complex components (generation plants, transmission network, distribution net-work, and loads) of electric power systems can benefit from the application of energy storage technologies to their respective operations. Table 1.1 from a previous study [13]

1000

Bataries

0.1r

1 10 00O

syuem Power Rating (MW)

Figure 1-3: Capability Comparison of Proposed Hydrogen Storage System to Existing Electricity Storage Technologies. Adapted from [12].

done by the United States Department of Energy (DOE) identified and defined the various applications of energy storage to power systems.

The applications identified by the DOE Study are similar to the benefits identified in this thesis. Since this thesis focuses on using seasonal storage to supply peak electricity, the discourse will be on how large-scale energy storage technologies can benefit the electrical power systems, specifically peak power generation and other ancillary services.

1.3.1 Responsive Energy Management

Traditionally, the electric power systems operate on the paradigm that energy produced must instantaneously match energy consumed. Seasonal storage enables the decoupling of demand and supply such that electricity does not necessarily have to be produced to instantaneously match the demand. With the availability of bulk energy storage technolo-gies, utilities can benefit from load leveling: a situation where the power variation between the minimum and peak demands is reduced because energy is stored during off-peak hours when the demand for electricity and its price are low and then dispatched during peak hours when the demand and the price are higher [14, 15].

Large-scale energy storage technologies can also be used to reduce or replace fossil-fueled intermediate or peaking power plant capacity by storing energy using base load plants operating at a much higher capacity output [7, 15]. The energy stored can subsequently be converted to electricity to provide for intermediate or peak generation. Utilities can also reduce or replace the capacity of units with much higher incremental heat or cost rate. The

Table 1.1: Definitions and Categories of Electric Power System Applications of Energy Storage [13]

Category Application Name and Definition

Generation Rapid Reserve

"Generation capacity that a utility holds in reserve to meet North Amer-ican Electricity Reliability Council (NERC) requirements to prevent in-terruption of service to customers in the event of a failure of an operating generating station."

Area Control and Frequency Responsive Reserve

"The ability for grid-connected utilities to prevent unplanned transfer of power between themselves and neighboring utilities (Area Control) and the ability of isolated utilities to instantaneously respond to frequency deviations (Frequency Responsive Reserve)."

Commodity Storage

"Storage of inexpensive off-peak power for dispatch during relatively expensive on-peak hours."

Transmission & Transmission System Stability

Distribution "Ability to keep all components on a transmission line in sync with each other and prevent system collapse."

Transmission Voltage Regulation

"Ability to maintain the voltages at the generation and load ends of a transmission line within five percent of each other."

Transmission Facility Deferral

"Ability of a utility to postpone installation of new transmission lines and transformers by supplementing the existing facilities with another

resource."

Distribution Facility Deferral

"Ability of a utility to postpone installation of new distribution lines and transformers by supplementing the existing facilities with another

resource."

Customer Customer Energy Management

Service "Dispatching energy stored during off-peak or low cost times to manage demand on utility-sourced power."

Renewable Energy Management

"Applications through which renewable power is available during peak utility demand (coincident peak) and available at a consistent level." Power Quality and Reliability

"Ability to prevent voltage spikes, voltage sags, and power outages that last for a few cycles (less than one second) to minutes from causing data and production loss for customers."

incremental heat rate (BTU2/kWh) is a measure of the efficiency of a generating unit for

each increment or block of power it produces [16]. The incremental cost rate ($/kWh) is simply the incremental heat rate multiplied by the corresponding fuel cost. Using cheap nuclear electricity to produce the storage medium (hydrogen) should result in a lower incremental cost rate for hydrogen peak electricity production.

Bulk energy storage technologies can also perform ramping or load following: a situation

where controls detect moment-by-moment fluctuations in electric demand and electric

supply capacity is provided to react instantly to match those variations [14, 15, 2]. Any large-scale storage technology that will perform the load-following function must have a rapid ramp rate - it must be able to change power output level rapidly [14]. Large-scale electricity storage technology can also act as a buffer which isolates the rest of the power grid or transmission network from frequent and rapid power changes [17] due to the use of very large inductive loads on the network.

The availability of large-scale electricity storage technologies can provide for energy im-balance -making up for supply-demand shortfalls [2]. Energy imbalance occurs when the actual demand exceeds the forecasted demand. Bulk energy storage can provide for such shortfalls without the utilities resorting to additional unit commitments. A unit commit-ment occurs when a generating unit is put online and made to provide power to the grid. Avoiding power plant commitment saves staffing and fuel costs [14]. Large-scale electric-ity storage technologies can also make up for real power losses [2] on the transmission or power grid.

Large-scale electricity storage technologies can benefit growing urban and suburban areas subject to dramatic day-time peaking if the large-scale energy storage systems are sited in these critical locations [18]. Rather than invest in distribution network upgrades, the energy storage systems can be charged locally during off-peak periods and discharged locally during peak periods. Even remote locations where it is impractical to site big central generating units can benefit from large-scale energy storage technologies [18] by using distributed energy sources coupled with scale storage technologies. A large-scale electricity storage system can also support a local distribution network during periods of "islanding" [15]. Power islanding occurs when a segment or portion of the distribution network becomes electrically isolated from the rest of the network but remains energized

by the distributed energy resources connected to the isolated subsystem [19].

1.3.2 Renewables Portfolio Management

Utilities that have renewable energy resources in their energy generation portfolio can ben-efit from large-scale storage technologies to smooth out the fluctuations in the intermittent supply typically associated with renewable energy generation. The storage systems will match the output from variable and relatively unpredictable energy resources with any demand profile [7, 18, 20] and aggregate "diluted energy" collected from dispersed solar

arrays and adapt it for use in power utilities [7]. With large-scale energy storage, excess production from renewable systems like wind or solar power systems can be directed to storage instead of dumping the excess energy or ramping down production from

fossil-2

fueled plants. Having a seasonal storage system coupled with nuclear and renewable sources enables utilities to maintain a diversified energy portfolio.

Large-scale electricity storage technologies enhance the economic value of renewable en-ergy resources by storing up the enen-ergy outputs of the renewable enen-ergy resources and time-shifting their consumption from low-demand periods when the value of electricity is low to peak demand periods when the price or value of electricity is much higher [17,21]. It also enhances the economic value of renewable energy resources by increasing the pre-dictabiliity of their future availability, since electric energy producers must guarantee the amount of power available for dispatch to the grid [21]. Rather than pay power grid op-erators to buy energy produced from wind power plants at night during period of lowest demand; a business practice allowed for wind power producers, for example, in the PJM3 electrical power grid [22], the excess energy can be stored using large-scale energy storage systems for such times when the energy can be sold for profit. With seasonal storage sys-tems, wind and solar power resources can have greater market penetration, as large-scale energy storage replaces intermittent erratic sources like wind or daylight-limited solar energy with a reliable predictable energy supply.

1.3.3 Contingency Reserves

In order to avoid a cascading blackout: a situation when a gross mismatch between de-mand and supply due to the loss of a large generator causes the remaining generators to become overloaded and automatically tripped off [2], system operators require that utilities have some operating or contingency reserve margin in the form of spinning reserves and supplemental reserves to cater for unanticipated system disruptions or outages. Seasonal storage systems with rapid ramp rates can provide for contingency reserves [14].

Spinning reserve is generation capacity held back for use and provided by operating several large plants at power output levels well below their maximum to ensure the availability of margin for output increase [14]. Spinning reserves can also be provided by generators that are online, synchronized with the grid, but unloaded; these generators can respond in the order of minutes to generation or transmission outages [17]. Such spinning reserve must provide for the loss of the largest generator in the system with minimal disruptions to the system power flow and frequency [17]. Generators providing supplemental reserves may be offline and are not required to be synchronized with the grid. Grids can also have access to supplemental reserves by curtailing the loads of large electrical consumers, thereby reducing demand [23]. Supplemental reserves are usually used after exhausting the capacity of the spinning reserves.

Using large-scale energy storage systems for spinning reserves eliminates the costs and greenhouse gas emissions associated with idling conventional generators for spinning reserves. Seasonal storage systems can also serve as backup supply to existing spinning reserve capacities.

3

The Pennsylvania-New Jersey-Maryland (PJM) Interconnection operates the electrical power grid for 13 states and the District of Columbia in the United States.

1.3.4 Enhanced Asset Management

The introduction of large-scale energy storage technologies to the power systems will allow for transmission and distribution (T&D) asset deferral. T&D asset deferral involves tem-porarily forgoing a transmission or distribution asset upgrade or acquisition by employing an electricity storage device. Such T&D assets include transmission lines, substations or their components. By storing energy during off-peak hours for subsequent consumption during peak hours, the transmission and distribution are relieved of possible overloading, thereby avoiding expensive transmission upgrades [14].

Since upgrade of the T&D assets is deferred, they are used for a much longer time. Storing energy during off-peak periods for consumption during peak periods reduces the power variation between the peak demands and off-peak demands, resulting in peak shaving or load leveling. With peak shaving, T&D are less frequently subjected to spikes, thereby extending their useful life. With large-scale storage, T&D assets are also utilized more efficiently due to their increased capacity factor. Seasonal storage results in improved flexibility, reliability, and efficiency of the electrical network.

1.3.5 Transmission Enhancement

Momentary voltage sags and surges, harmonic distortions, and other imperfections can be smoothed out or stabilized by energy storage systems with rapid ramp rates coupled with advanced power electronics [24]. By providing line stability, voltage regulation, and phase angle control, energy storage can also enhance transmission capacity and improve the load carrying capacity of the transmission system [24, 17]. Energy storage can also provide frequency regulation that occurs due to mismatch between electricity supply and demand on the power grids.

1.3.6 Economic Value

Energy storage provides arbitrage opportunities for power producers. Arbitrage involves buying inexpensive electricity when its demand and cost are low; and then selling the electricity for profit when the demand and cost are high. Consumers also benefit econom-ically from lowered energy costs [25]. Large-scale energy storage can help minimize the impact of price volatility caused by natural gas supply disruptions to the intermediate and peaking natural gas plants [25]. Large-scale storage can also mitigate the effect of price shocks by reducing the increase in on-peak electricity prices [25]. By deploying large-scale energy storage systems, utilities can avoid congestion charges.

1.3.7 Environmental Impacts

Large-scale energy storage enables utilities to avoid starting up and running fossil-fuel plants at part load, thereby reducing fossil fuel use and greenhouse gas emissions per kWhe generated [14]. Running power plants at part load provides for load following and spinning reserves. Large-scale energy storage systems can replace fossil fuel plants to provide these services. By using zero CO2emission large-scale energy storage technologies,

the environment benefits from avoiding the large amount of carbon dioxide that would have been emitted if fossil-fueled plants had been used instead. Since large-scale energy storage enables a greater penetration of renewable energy sources into the electrical grid, more fossil-fueled plants are displaced by the increased output from the renewable sources. Developing a seasonal storage system that uses hydrogen for peak electricity production instead of fossil - fueled peaking plants will in addition to expanding the application of nuclear energy to new markets, help reduce the environmental impacts associated with the combustion of fossil fuels, particularly the emission of carbon dioxide.

1.4 Thesis Objectives

The ultimate objective of the work on seasonal storage hydrogen peak electricity supply system (SSHPESS) is the design of an optimal hydrogen-fueled production, storage and generation system that will provide electric power to the electric grid during periods of peak electricity demand. The SSHPESS design effort will also produce an optimal solution suitable for near-term deployment as well as one suitable for long-term deployment. In addition, the work will describe component designs for the hydrogen and oxygen storage subsystems.

The objectives of this thesis include developing the system requirements for the seasonal storage hydrogen peak electricity supply system. The system requirements include func-tional, performance, and interface requirements for the system. While the functional requirements dictate what the system must do, the performance requirements specify how well the system must do what it is designed to do. The interface requirements specify how the various subsystems relate and integrate with one another. The system requirements also identify design constraints, which may limit design flexibility. These design constraints include regulatory standards; limitations imposed by the physics of the problems; limits imposed by choice of materials; safety requirements, and site or location constraints. One of the key elements of the design work is the development of the functional architecture of the system. The functional architecture is derived by the decomposition of higher-level functions and performance requirements identified through requirements analysis into lower-level functions and performance requirements [26]. It is these lower-level functions that are arranged ina logical sequence and aggregated together to make system components or subsystems. This particular element provides the essential information to developing the optimal physical architecture [26].

This work also involves the development of the physical architecture, the technical spec-ifications, baselines and key performance measures for the seasonal storage hydrogen peak electricity supply system and its subsystems. The physical architecture may employ currently available commercial-off-the-shelf technologies or technologies that are still in the research and development (R&D) stage. Where deemed necessary, new technology concepts will be proposed if those concepts have the potential of being more technically optimal and economically viable than existing technologies. The physical architecture will be proposed based on different timescales of deployment, namely near-term and long-term deployment. A near-term solution means that the solution can be deployed immediately using existing technologies. A long-term solution means that such a solution will be fea-sible for deployment in the near-future by using technologies already in the research and