Preface xiii
1 Overview of Current Development and Research Trends in Energy Storage Technologies 1
O. Apata
1.1 Introduction 1
1.2 The Technology of Energy Storage 4
1.3 Energy Storage and Smart Grids 14
1.4 Energy Storage and Micro-Grids 15
1.5 Energy Storage Policy Recommendations 17
1.6 Energy Storage: Challenges and Opportunities 18
1.7 Practical Implementations of Energy Storage Technologies 19
1.8 Conclusions 20
References 20
2 A Comprehensive Review of the Li-Ion Batteries Fast-Charging Protocols 23
Talal Mouais and Saeed Mian Qaisar
2.1 Introduction 24
2.2 The Literature Review 27
2.2.1 Overview of Lithium-Ion Battery Working Principle 28
2.2.2 Principles of Battery Fast-Charging 31
2.2.3 Multi-Scale Design for Fast Charging 33
2.2.4 Electrode Materials 33
2.2.5 Fast-Charging Strategies 34
2.2.6 Types of Charging Protocols 34
2.2.7 Li-Ion Battery Degradation 40
2.2.8 Factors that Cause Battery Degradation 41
2.2.9 Degradation Mechanism of the Li-Ion Battery 44
2.2.10 Electrode Degradation in Lithium-Ion Batteries 48
2.2.11 The Battery Management System 50
2.2.12 Battery Technology Gap Assessment for Fast-Charging 53
2.2.13 Developmental Needs 55
2.3 Materials and Methods 56
2.4 Discussion 58
2.5 Conclusion 63
Acknowledgements 65
References 65
3 Development of Sustainable HighPerformance Supercapacitor Electrodes from Biochar-Based Material 71
Kriti Shrivastava and Ankur Jain
3.1 Introduction 72
3.2 Role of Energy Storage Systems in Grid Modernization 73
3.3 Overview of Current Developments of Supercapacitor-Based Electrical Energy Storage Technologies 78
3.4 Potential of Biochar as High-Performance Sustainable Material 80
3.5 Overview of Recent Developments in Biochar-Based EDLC Supercapacitor 83
3.5.1 Wood& Plant Residues as Biochar Precursor for Supercapacitor Applications 84
3.5.2 Biochar-Based Supercapacitors from Waste Biomass 89
3.5.3 Carbon-Based Supercapacitors from Other Methods 91
3.6 Current Challenges and Future Potential of Biochar-Based Supercapacitor 93
3.7 Conclusion 99
References 101
4 Energy Storage Units for Frequency Management in Nuclear Generators-Based Power System 105
Boopathi D., Jagatheesan K., Sourav Samanta, Anand B. and Satheeshkumar R.
4.1 Introduction 105
4.1.1 Structure of the Chapter 110
4.1.2 Objective of the Chapter 110
4.2 Investigated System Modeling 111
4.2.1 Battery Energy Storage System (BESS) Model 112
4.2.2 Fuel Cell (FC) Model 113
4.2.3 Redox Flow Battery (RFB) Model 113
4.2.4 Proton Exchange Membrane (PEM) Based FC Model 114
4.2.5 Ultra-Capacitor (UC) Model 115
4.2.6 Supercapacitor Energy Storage (SCES) Model 116
4.3 Controller and Cost Function 116
4.4 Optimization Methodology 118
4.5 Impact Analysis of Energy Storage Units 119
4.5.1 Impact of BESS 119
4.5.2 Impact of FC 121
4.5.3 Impact of RFB 122
4.5.4 Impact Analysis of the PEM-FC 123
4.5.5 Impact Analysis of UC 125
4.5.6 Impact Analysis of SCES 127
4.6 Result and Discussion 128
4.7 Conclusion 130
Appendix 132
References 132
5 Detailed Comparative Analysis and Performance of Fuel Cells 135
Tejinder Singh Saggu and Arvind Dhingra
5.1 Introduction 135
5.2 Classification of Fuel Cells 136
5.2.1 Based on Fuel-Oxidizer Electrolyte 138
5.2.1.1 Direct Fuel Cell 138
5.2.1.2 Regenerative FC 139
5.2.1.3 Indirect Fuel Cells 143
5.2.2 Based on the State of Aggregation of Reactants 144
5.2.2.1 Solid Fuel Cells 144
5.2.2.2 Gaseous Fuel Cells 145
5.2.2.3 Liquid Fuel Cells 147
5.2.3 Based on Electrolyte Temperature 148
5.2.3.1 Proton Exchange Membrane 148
5.2.3.2 Direct Methanol 150
5.2.3.3 Alkaline 150
5.2.3.4 Phosphoric Acid 151
5.2.3.5 Molten Carbonate 152
5.2.3.6 Solid Oxide 153
5.3 Cost of Different Fuel Cell Technologies 154
5.4 Conclusion 155
References 155
6 Machine LearningBased SoC Estimation: A Recent Advancement in Battery Energy Storage System 159
Prerana Mohapatra, Venkata Ramana Naik N. and Anup Kumar Panda
6.1 Introduction 160
6.2 SoC Estimation Techniques 163
6.2.1 Coulomb Counting Approach 164
6.2.2 Look-Up Table Method 164
6.2.3 Model-Based Methods 164
6.2.3.1 Electrochemical Model 164
6.2.3.2 Equivalent Circuit Model 165
6.2.4 Data-Driven Methods 165
6.2.5 Machine LearningBased Methods 166
6.2.5.1 Support Vector Regression 166
6.2.5.2 Ridged Extreme Learning Machine (RELM) 168
6.3 BESS Description 171
6.4 Results and Discussion 171
6.5 Conclusion 175
References 177
7 Dual-Energy Storage System for Optimal Operation of GridConnected Microgrid System 181
Deepak Kumar and Sandeep Dhundhara
7.1 Introduction 182
7.2 System Mathematical Modelling 188
7.2.1 Modelling of Wind Turbine Power Generator 189
7.2.2 Modelling of Solar Power Plant 189
7.2.3 Modelling of Conventional Diesel Power Generator 189
7.2.4 Modelling of Combined Heat and Power (CHP) and Boiler Plant 190
7.2.5 Modelling of Dual Energy Storage System 190
7.2.5.1 Battery Bank Storage System 190
7.2.5.2 Pump Hydro Storage System 191
7.2.6 Modelling of Power Transfer Capability 191
7.3 Objective Function and Problem Formulations 192
7.3.1 Operational and Technical Constraints 192
7.4 Simulation Results and Discussion 195
7.5 Conclusion 208
References 209
8 Applications of Energy Storage in Modern Power System through Demand-Side Management 213
Preeti Gupta and Yajvender Pal Verma
8.1 Introduction to Demand-Side Management 214
8.1.1 Demand-Side Management Techniques 214
8.1.1.1 Energy Efficiency 214
8.1.1.2 Demand Response 215
8.1.2 Demand-Side Management Approaches 217
8.2 Operational Aspects of DR 218
8.3 DSM Challenges 221
8.4 Demand Response Resources 223
8.5 Role of Battery Energy Storage in DSM 224
8.5.1 Case Study I: Peak Load and PAR Reduction 225
8.5.1.1 Problem Formulation 225
8.5.1.2 Energy Storage Dispatch Modelling 226
8.5.2 Case Study II: Minimizing Load Profile Variations 229
8.5.2.1 Problem Formulation 229
8.5.2.2 SPV System Modelling 230
8.5.3 Results and Discussions 231
8.5.3.1 Case Study I: Peak Load and PAR Reduction Using Batteries with DR 231
8.5.3.2 Case Study II: Minimizing Load Profile Variations Using Batteries with DR 232
8.6 Conclusion 234
References 234
9 Impact of Battery Energy Storage Systems and Demand Response Program on Locational Marginal Prices in Distribution System 239
Saikrishna Varikunta and Ashwani Kumar
9.1 Introduction 240
9.1.1 Battery Energy Storage System (BESS) 240
9.1.2 Demand Response Program 242
9.2 Problem Formulation and Solution Using GAMS 244
9.2.1 Objective Functions for Case Studies: Case 1 to Case 5 245
9.2.1.1 Case 1: Is Minimization of the Active Power Production Cost 245
9.2.1.2 Case 2: Minimization of the Active Power Production and Reactive Power Production Cost 246
9.2.1.3 Case 3: Minimization of the Active Power Production and Reactive Power Production Cost Along with Capacitor Placement 246
9.2.1.4 Case 4: Minimization of the Active Power Production and Reactive Power Production Cost Including Capacitor and BESS Cost 247
9.2.1.5 Case 5: Minimization of the Active Power Production and Reactive Power Production Cost Including Capacitor and BESS Cost and Taking the Impact of Demand Response Program 248
9.2.2 Real and Reactive Power Equality Constraints 249
9.2.2.1 Equality Constraints 249
9.2.2.2 Inequality Constraints: (at any bus i): Voltage, Power Generation, Line Flow, SOC, Battery Energy Storage Power 250
9.2.3 Modified Lagrangian Function 251
9.2.4 Generator Economics Calculations 252
9.3 Case Study: Numerical Computation 254
9.4 Results and Discussions 257
9.4.1 Case 1: Minimization of the Active Power Production Cost 257
9.4.2 Case 2: Minimization of the Active Power Production and Reactive Power Production Cost 260
9.4.3 Case 3: Minimization of the Active Power Production and Reactive Power Production Cost Along 262
9.4.4 Case 4: Minimization of the Active Power Production and Reactive Power Production Cost 266
9.4.5 Case 5: Minimization of the Active Power Production and Reactive Power Production Cost 269
9.5 Conclusions 279
References 280
10 Cost-Benefit Analysis with Optimal DG Allocation and Energy Storage System Incorporating Demand Response Technique 283
Rohit Kandpal, Ashwani Kumar, Sandeep Dhundhara and Yajvender Pal Verma
10.1 Introduction 284
10.2 Distribution Generation and Energy Storage System 285
10.2.1 Renewable Energy in India 286
10.2.2 Different Types of Energy Storage and their Opportunities 287
10.2.3 Distributed Generation 290
10.2.3.1 Solar Photovoltaic Panel-Based DG (PVDG) 290
10.2.3.2 Wind TurbineBased DG (WTDG) 291
10.2.3.3 Load Model and Load Profile 293
10.2.4 Demand Response Program 294
10.2.5 Electric Vehicles 297
10.2.6 Modeling of Energy Storage System 299
10.2.7 Problem Formulation 300
10.2.8 Distribution Location Marginal Pricing 301
10.3 Grey Wolf Optimization 302
10.4 Numerical Simulation and Results 304
10.5 Conclusions 312
References 313
11 Energy Storage Systems and Charging Stations Mechanism for Electric Vehicles 317
Saurabh Ratra, Kanwardeep Singh and Derminder Singh
11.1 Introduction to Electric Vehicles 318
11.1.1 Role of Electric Vehicles in Modern Power System 318
11.1.2 Various Storage Technologies 319
11.1.3 Electric Vehicle Charging Structure 322
11.2 Introduction to Electric Vehicle Charging Station 323
11.2.1 Types of Charging Station 323
11.2.2 Charging Levels 324
11.2.3 EV Charging 324
11.2.4 Charging Period 327
11.3 Modern System Efficient Approches 328
11.3.1 Smart Grid Technology 328
11.3.2 Renewable Energy Technology 329
11.3.3 V2G Technology 329
11.3.4 Smart Transport System 329
11.4 Battery Charging Techniques 330
11.4.1 Electric Vehicle Charging Station in Modern Power System 331
11.5 Indian Scenario 332
11.6 Energy Storage System Evaluation for EV Applications 333
11.7 ESS Concerns and Experiments in EV Solicitations 334
11.7.1 Raw Materials 335
11.7.2 Interfacing by Power Electronics 335
11.7.3 Energy Management 335
11.7.4 Environmental Impact 336
11.7.5 Safety 336
11.8 Conclusion 336
References 337
Index 341
