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Artificial Intelligence for Sustainable Energy Systems 1
Intelligent Technologies for Sustainable Energy Management
Inam Ul Haq (Edited by), I Ul Haq (Author), Sanna Mehraj Kak (Edited by), Anand Kumar Gupta (Edited by), Muhammad Sher Ramzan (Edited by)
9781836690979, Wiley
Hardback, published 12 June 2026
304 pages
23.5 x 15.6 x 2 cm, 0.564 kg
Artificial Intelligence for Sustainable Energy Systems 1 presents a comprehensive exploration of how intelligent technologies are transforming modern energy infrastructures toward a more sustainable and efficient future.
This book brings together the fundamental concepts of artificial intelligence (AI), machine learning, deep learning and big data analytics, with their practical integration into renewable energy systems, smart grids and digital energy management platforms. The book covers key developments such as AI-driven renewable optimization, predictive modeling for energy demand, digital twins for asset maintenance, blockchain-enabled energy trading, IoT-based smart grids and intelligent monitoring systems. By blending theoretical insights with real-world technological implementations, the book highlights how data-driven intelligence enhances reliability, security and sustainability across energy ecosystems.
Designed for researchers, engineers, graduate students and policymakers, this book serves as a fundamental reference for advancing intelligent solutions in next-generation sustainable energy systems.
Preface xv Chapter 1. Introduction to Sustainable Energy Systems 1 1.1. Introduction 1 Chapter 2. Overview of AI, ML and DL Applications in Energy and Sustainability 17 2.1. Introduction 17 Chapter 3. Overview of AI, ML and DL Applications in Energy and Sustainability 37 3.1. Introduction 37 Chapter 4. Conceptual and Methodological Insights into AI, ML and DL for Energy and Environmental Challenges 51 4.1. Introduction 52 Chapter 5. AI in Renewable Energy Technologies 89 5.1. Introduction to sustainable energy systems 89 Chapter 6. Big Data Analytics and Predictive Models in Energy Systems 121 6.1. Introduction 121 Chapter 7. Smart Grids, IoT and AI: Transforming Energy Management for a Sustainable Future 161 7.1. Introduction 162 Chapter 8. Digital Twins and AI for Predictive Maintenance of Renewable Energy Assets 177 8.1. Introduction 177 Chapter 9. Digitally Enhanced Fire Alarm System Using Sensor Driven Arduino Implementation for Smart Energy Management 197 9.1. Introduction 198 Chapter 10. AI and Blockchain for Renewable Energy Trading 215 10.1. Introduction 215 Chapter 11. Smart Energy Grids: Architecture, Security and Emerging Technologies 241 11.1. Introduction 241 List of Authors 257
Inam UL HAQ, Sanna Mehraj KAK, Anand Kumar GUPTA and Muhammad Sher RAMZAN
Inam UL HAQ
1.2. Components of sustainable energy systems 4
1.3. Sustainability issues in energy 7
1.4. AI in sustainable energy systems 8
1.5. Case studies and applications 11
1.6. Future directions 13
1.7. Conclusion 14
1.8. References 15
Priya PANDEY, Ashish PANDEY and Hema MAHAWAR
2.2. Literature review 25
2.3. Methodology 27
2.4. Challenges 30
2.5. Conclusion and future scope 32
2.6. References 33
Mrinal PANDEY and Monika GOYAL
3.2. Literature survey 39
3.3. Brief description of AI, ML and DL 40
3.4. Applications of AI in energy sectors and sustainability 42
3.5. Case study 45
3.6. Conclusion 49
3.7. References 49
Inderdeep KAUR
4.2. Conceptual foundations of AI, ML and DL 57
4.3. Methodologies for environmental data acquisition 64
4.4. AI-based predictive modeling for environmental challenges 68
4.5. AI-driven energy system optimization 73
4.6. Smart agriculture and precision forestry 76
4.7. Challenges and ethical considerations 78
4.8. Future directions and emerging trends 81
4.9. Conclusion 83
4.10. References 84
Jagdeep KAUR, Vidhi GUPTA and Aditi RAJ
5.2. Introduction to AI in renewable energy technologies 94
5.3. Smart grids, IoT and AI for energy management 99
5.4. Global policies and AI-enabled energy strategies 106
5.5. Future directions, pathways to net-zero: challenges, risks and future of AI in sustainable energy 114
5.6. Conclusion 118
5.7. References 119
Biswajit DAS, Himanshu PABBI, Shweta SINGH, Monika MEHRA and Sanny KUMAR
6.2. Big data analytics in energy systems basics 126
6.3. Predictive modeling: concepts and techniques 131
6.4. Applications of big data analytics in energy systems 140
6.5. Integration of IoT, Edge and cloud technologies 144
6.6. Case studies and real-world implementations 147
6.7. Challenges, limitations and future directions 150
6.8. Conclusion 154
6.9. References 156
Khalid Hafiz MIR and Anzah BASHIR
7.2. Ethical considerations 164
7.3. Regulatory frameworks 170
7.4. Metrics for ethical and regulatory compliance 172
7.5. Future directions 173
7.6. Conclusion 173
7.7. References 174
Abdul Malik ANSARI
8.2. DTs in renewable energy 179
8.3. System architecture of DT–AI integration 183
8.4. Integration of DTs and AI 185
8.5. Comparative analysis of maintenance strategies 192
8.6. Conclusion 194
8.7. References 194
Ranjit Kumar BINDAL and Akhil NIGAM
9.2. Literature review 198
9.3. Problem formulation 201
9.4. Constraints 202
9.5. Advantages of Arduino Uno over other types of Arduino modules 207
9.6. Concluding remarks 210
9.7. References 211
Hitendra SINGH, Pradeep Kumar SHARMA, Deepti GUPTA, Fardeen Ahmad KHAN, Bandana KUMARI, Shivani SHARMA, Prashant KUMAR and Sanny KUMAR
10.2. AI in renewable energy 218
10.3. Renewable energy with blockchain 220
10.4. AI–blockchain synergy 226
10.5. Challenges and limitations in blockchain and AI-based renewable energy trading 230
10.6. Future prospects 233
10.7. Summary 236
10.8. References 237
Dhruv GOEL, Pratham KUMAR, Mamta NARWARIA and Md Jauhar IMAM
11.2. Literature review/background 242
11.3. IoT-enabled smart energy grid framework (methodology) 245
11.4. Results and discussion 248
11.5. Security vulnerabilities and threat models 249
11.6. Challenges and future scope 252
11.7. Conclusion 254
11.8. References 255
Index 261
Subject Areas: History [HB]
