Preface xiii 1 Overview of Current Development and Research Trends in Energy Storage Technologies 1O. 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 23Talal 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 High‑Performance Supercapacitor Electrodes from Biochar-Based Material 71Kriti 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 105Boopathi 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 135Tejinder 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 Learning–Based SoC Estimation: A Recent Advancement in Battery Energy Storage System 159Prerana 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 Learning–Based 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 Grid‑Connected Microgrid System 181Deepak 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 213Preeti 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 239Saikrishna 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 283Rohit 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 Turbine–Based 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 317Saurabh 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

Written and edited by a team of experts, this exciting new volume discusses the various types of energy storage technologies, the applications of energy storage systems, their role in the real-time operation of power markets, and the operational issues of modern power systems, including renewable-based generating sources. The worldwide energy sector, specifically power generation, has undergone a huge transformation in recent years, and the focus is to make it sustainable, environmentally friendly, reliable, and highly efficient. As a result, a significant share of highly intermittent but clean renewable sources is being integrated into the power system using advanced technological components. The higher penetration level of renewable energy sources (RESs) has increased the active power generation share in the grid but reduced the total rotating system inertia. This high reduction in inertia brings new challenges and technical issues to the operators of modern power systems and impacts the stability and security of the grid. The stochasticity of these renewable sources also poses a big challenge to the efficient operation of the power system. Electrical energy storage systems help to manage such issues and challenges that occur due to the intermittent nature of RES and can play a big role in the smooth and reliable operation of the power system. The applications and opportunities to use storage on the grid are growing due to the improvements in energy storage technologies, and flexible regulatory frameworks. Technological developments have made it possible to use batteries and other Energy Storage Systems (ESSs) for managing the operation of the power system. This book aims to illustrate the potential of energy storage systems in different applications of the modern power system considering recent advances and research trends in storage technologies. These areas are going to play a very significant role in future smart grid operations. This book discusses the various types of energy storage technologies and promotes the applications of ESSs in the performance improvement of modern power systems. Whether for the veteran engineer, new hire, or student, it is a must-have for any library.