Artificial Intelligence for Energy Management

Preface xvii

1 Introduction to Next-Generation Energy Management and Need for AI Solutions 1
D. Gunapriya, P. Vinoth Kumar, G. Banu, S. Revathy, S. Giriprasad and N. Pushpalatha

1.1 Introduction 2
1.2 Application of AI in Energy Management Revolution 5
1.3 AI in Energy Sector 6
1.4 Role of AI in Energy Efficiency Improvement 7
1.5 Role of AI in Demand Forecasting and Load Balancing 7
1.6 Enhanced Sustainability and Reduced Carbon Footprint 8
1.7 AI-Based Grid Stability Enhancement 8
1.8 Predictive Maintenance and Asset Management 9
1.9 AI-Powered Energy Trading and Price Optimization 9
1.10 Ethical Considerations in AI-Powered Energy Management 10
1.11 Challenges in Incorporating AI in EMS 13
1.12 Case Studies on Implementing AI for Future Energy Management 18
1.13 Future Research Directions 21
1.14 Conclusion 23

2 Overview of Innovative Next Generation Energy Storage Technologies 27
D. Magdalin Mary, G. Sophia Jasmine, V. Vanitha, C. Kumar and T. Dharma Raj

2.1 Introduction 28
2.2 Energy Storage Techniques 29
2.3 Mechanical Energy Storage System 35
2.4 Electrochemical Storage System 35
2.5 Thermal Storage System 36
2.6 Electrical Energy Storage System 37
2.7 Hydrogen Storage System (Power-to-Gas) 37

3 Battery Energy Storage Systems with AI 39
Ashadevi S. and Latha R.

3.1 Introduction 39
3.2 System for Managing Batteries 41
3.3 Demand Response Strategies 52
3.4 Battery Energy Storage System 53
3.5 Technical Overview of Battery Energy Storage System 54
3.6 Conclusion and Future Scope 60

4 AI-Powered Strategies for Optimal Battery Health and Environmental Resilience for Sodium Ion Batteries 65
Sujith M., Pardeshi D.B., Krushna Lad, Pratiksha Ahire and Karun Pagetra

4.1 Introduction 66
4.2 Cathode Material 68
4.3 Anode Material 71
4.4 Electrolyte 73
4.5 State of Discharge (SOD) 75
4.6 State of Health (SOH) 76
4.7 BMS Algorithm with AI for SOH 77
4.8 Conclusion 79

5 Design and Development of an Adaptive Battery Management System for E-Vehicles 83
Saravanan Palaniswamy, Anbuselvi Mathivanan, A. Siyan Ananth and Sonu R.

5.1 Introduction 84
5.2 Related Works 85
5.3 Simulation Design 87
5.4 System Design 89
5.5 Implementation 95
5.6 Experimental Results 96
5.7 Conclusion 98

6 Remaining Useful Life (RUL) Prediction for EV Batteries 101
Anbuselvi Mathivanan, Saravanan Palaniswamy and M. Arul Mozhi

6.1 Introduction 102
6.2 Related Works 105
6.3 Proposed Model 106
6.4 Hardware Implementation 115
6.5 Outcomes and Analysis 120
6.6 Conclusion 124

7 Analysis of Si, SiC, and GaN MOSFETs for Electric Vehicle Power Electronics System 129
K. Praharshitha, Varun S., Rithick Sarathi M.B. and V. Indragandhi

7.1 Introduction 129
7.2 Literature Survey 130
7.3 Technical Specification 132
7.4 Methodology 133
7.5 Project Demonstration 133
7.6 Results 135

8 An Efficient Control Strategy for Hybrid Electrical Vehicles Using Optimized Deep Learning Techniques 141
V. Vanitha, G. Sophia Jasmine and D. Magdalin Mary

8.1 Introduction 142
8.2 Approaches in Charging Optimization 144
8.3 System Model 145
8.4 Proposed Methodology 146
8.5 Results and Discussion 153
8.6 Conclusion 162

9 Machine Learning and Deep Learning Methods for Energy Management Systems 165
V. Manimegalai, P. Ravi Raaghav, V. Mohanapriya, T.R. Vashishsdh and S. Palaniappan

9.1 Introduction 166
9.2 Building Energy Management System 167
9.3 Grid Optimization 173
9.4 Intelligent Energy Storage 184
9.5 Roles of ML and DL 199
9.6 The Roles of Traditional Methods in Energy Management System 204
9.7 Conclusion 209

10 Ensuring Grid-Connected Stability for Single-Stage PV System Using Active Compensation for Reduced DC-Link Capacitance 213
Deepika Amudala and P. Buchibabu

10.1 Introduction 213
10.2 Modeling of Grid-Tied PV 215
10.3 MATLAB Simulation Design and Results 216
10.3.1 Simulations Results 217
10.4 Comparison of THD (Total Hormonic Distortion) Values Between PI and ANN 222
10.5 Conclusion 223

11 Optimizing Microgrid Scheduling with Renewables and Demand Response through the Enhanced Crayfish Optimization Algorithm 225
Karthik Nagarajan, Arul Rajagopalan and Priyadarshini Ramasubramanian

11.1 Introduction 226
11.2 Problem Formulation 227
11.3 Enhanced Crayfish Optimization Algorithm 234
11.4 Fuzzy Logic-Based Selection of Optimal Compromise Solution 239
11.5 Results and Discussion 240
11.6 Conclusion 244

12 Relative Investigation of Swarm Optimized Load Frequency Controller 247
Sheema B. S. P., Peer Fathima A. and Stella Morris

12.1 Introduction 248
12.2 Methodology 250
12.3 Simulation Results and Discussions 257
12.4 Conclusion 261

13 Economic Aspects and Life Cycle Assessment in Energy Storage Systems 263
Pandiyan P., Senthil Kumar R., Saravanan S. and P. Balakumar

13.1 Introduction 264
13.2 Types of Energy Storage Systems 265
13.3 Life Cycle Assessment (LCA) in Energy Storage Systems 271
13.4 AI in Economic Optimization and Life Cycle Management (LCA) 277
13.5 Challenges and Future Directions 284
13.6 Conclusion 286

14 Energy Monitoring System Using Arduino and Blynk: Design and Simulation 291
Pilla Krishna Satwik, Samartha and Sritama Roy

14.1 Introduction 291
14.2 Motivations 293
14.3 System Architecture 295
14.4 Design and Implementation 297
14.5 Experimental Evaluation 302
14.6 Conclusion 304

15 Smart Home Energy Management System 307
A. R. Kalaiarasi, T. Deepa and S. Angalaeswari

15.1 Introduction 307
15.2 Arduino UNO 310
15.3 Bluetooth Module 310
15.4 Relay Module 311
15.5 Android Application 312
15.6 Software 313
15.7 Flow Diagram 313
15.8 Hardware Implementation 314
15.9 Results and Discussion 315
15.10 Conclusion 317

16 A Study to Analyze the Vulnerabilities and Threats Faced by the Power Sector 319
A. R. Kalaiarasi and Aishwarya G. P.

16.1 Introduction 319
16.2 Analyzing the Risk Index of Threats with Case Study 321
16.3 Cyber Vulnerabilities of Power System Case Study 326
16.4 Conclusion 332

17 Integrated Hybrid Energy Management to Reduce Standby Mode Power Consumption 335
N. Amuthan, N. Sivakumar and B. Gopal Samy

17.1 Introduction 336
17.2 Standby Power Regulations and Standards 338
17.3 Theoretical Framework for Standby Power Reduction 340
17.4 Energy Harvesting and Standby Power 342
17.5 Power Factor Correction (PFC) and Standby Power 344
17.6 Zero Standby Power Solutions 345
17.7 Control Strategies for Power Converters 347
17.8 Software Approaches to Standby Power Reduction 350
17.9 Electromagnetic Interference (EMI) and Standby Power 351
17.10 Cost-Benefit Analysis of Standby Power Reduction 353
17.11 Consumer Electronics and Standby Power 355
17.12 Integration of IoT Devices with Power Converters 357
17.13 Policy Implications and Advocacy for Standby Power Reduction 358
17.14 Educational Initiatives for Standby Power Awareness 360
17.15 Conclusion 362

18 Enhanced Reliability of Electrical Power Transmission in IEEE 24 DC Bus System Using Hybrid Optimization 371
Shereena Gaffoor and Mariamma Chacko

18.1 Introduction 372
18.2 Hybrid Optimization Model Combining GWO and GA 374
18.3 System Description and Model Implementation 375
18.4 Reliability Factors Considered 377
18.5 Conclusion 382

19 Impact of Renewable Energy Sources on Power System Inertia 385
M. Chethan, Ravi Kuppan, M. Dharani and M. Kalpana

19.1 Introduction 386
19.2 VSG: Integration, Modeling, and Controller Structure 389
19.3 Simulation Results and Discussion 392
19.4 Conclusion 395

20 Empowering India Toward Sustainability: An In-Depth Review of Wind Energy Utilization 399
Shibin Shaji John, Heyrin Ann Sony, Ahan Vincent Michael and Sitharthan Ramachandran

20.1 Introduction 400
20.2 Global Status of Wind Energy 401
20.3 Wind Energy Potential in India 404
20.4 Wind Energy Production Capacity in India 405
20.5 Indian Wind Energy Policy for Promoting Installation 411
20.6 Conclusion 412

References 412
About the Editors 415
Index 417