Artificial Intelligence for Next-Generation Energy Systems
Sustainable, Secure, and Intelligent Solutions
- 1st Edition - May 1, 2027
- Latest edition
- Editors: Fausto Pedro Garcia Marquez, Mariya Ouaissa, Hemant Kumar Saini, Mariyam Ouaissa
- Language: English
Artificial Intelligence for Next-Generation Energy Systems: Sustainable, Secure, and Intelligent Solutions provides guidance on leveraging A.I. to address challenges for renewa… Read more
Description
Description
Artificial Intelligence for Next-Generation Energy Systems: Sustainable, Secure, and Intelligent Solutions provides guidance on leveraging A.I. to address challenges for renewable integration in modern energy systems. The increasing complexity of modern power systems creates a need for intelligent, scalable, and adaptive solutions. This book distinguishes itself by consolidating AI-driven innovations and advances, technical insights, and practical industrial case studies to enable readers to create these effective solutions.
Chapters review innovative technologies including machine learning, deep learning, optimization, and big data analytics to enable intelligent forecasting and fault detection. Case studies demonstrate the application of these technologies for renewable energy integration, electric vehicle integration, and energy storage and distribution, and common challenges such as rid resilience, demand forecasting, and cyber-secure energy management. The book's diverse range of authorship presents challenges and solutions for energy systems across a variety of geographic regions and infrastructures. Social, ethical considerations, and future challenges for the integration of A.I. into energy systems are also included.
This book is valuable for academics, researchers, professors, and graduate students working on artificial intelligence, energy engineering, and sustainable technologies. Industry professionals developing next-generation energy systems in labs, universities, and technical institutes will also benefit from this volume.
Chapters review innovative technologies including machine learning, deep learning, optimization, and big data analytics to enable intelligent forecasting and fault detection. Case studies demonstrate the application of these technologies for renewable energy integration, electric vehicle integration, and energy storage and distribution, and common challenges such as rid resilience, demand forecasting, and cyber-secure energy management. The book's diverse range of authorship presents challenges and solutions for energy systems across a variety of geographic regions and infrastructures. Social, ethical considerations, and future challenges for the integration of A.I. into energy systems are also included.
This book is valuable for academics, researchers, professors, and graduate students working on artificial intelligence, energy engineering, and sustainable technologies. Industry professionals developing next-generation energy systems in labs, universities, and technical institutes will also benefit from this volume.
Key features
Key features
• Presents comprehensive, research-oriented guidance on A.I. for designing intelligent renewable energy systems
• Demonstrates practical deployment of intelligent energy systems through case studies
• Provides a framework for strategic decision-making and solutions for energy efficiency, cost reduction, and sustainability
• Demonstrates practical deployment of intelligent energy systems through case studies
• Provides a framework for strategic decision-making and solutions for energy efficiency, cost reduction, and sustainability
Readership
Readership
Academics, Researchers, and Graduate Students working in AI-driven intelligent systems and next-generation energy solutions, Artificial Intelligence, Energy Engineering, Computer Science, and Sustainable Technologies
Table of contents
Table of contents
Part I – Foundations and Emerging Paradigms
1. Introduction: Artificial Intelligence for Next Generation Energy Systems Overview of AI techniques, energy transition challenges, digital transformation, and book roadmap
2. Machine Learning and Deep Learning in Energy Applications Fundamental algorithms, supervised/unsupervised learning, neural networks, reinforcement learning for forecasting and optimization
3. Big Data Analytics and Energy Intelligence Data-driven modeling, cloud and edge computing, handling high-dimensional datasets in energy systems
4. Quantum Computing for Future Energy Systems Role of quantum algorithms in optimization, simulation, and secure energy trading
Part II – AI in Energy Infrastructure
5. Smart Grids and Intelligent Distribution Systems AI for grid monitoring, dynamic pricing, fault detection, and grid automation
6. Renewable Energy Forecasting, PV System Optimization, and Integration in Smart Grids Solar/wind energy prediction models, hybrid approaches, uncertainty management in renewable-heavy grids including challenges of high renewable penetration and energy communities with distributed PV systems
7. AI for Energy Storage, Home Energy Management Systems, and Intelligent Control Intelligent charging/discharging strategies, HEMS, demand-side optimization, predictive maintenance, and energy resilience
8. IoT, Edge, and Cloud AI in Energy Systems Cyber-physical integration, real-time decision-making, digital twins for power systems
Part III – Security, Sustainability, and Society
9. Cybersecurity in AI-driven Energy Systems Threat modeling, anomaly detection, adversarial AI, and blockchain-based solutions
10. AI for Energy Market Optimization, Energy Communities, and Trading Bidding strategies, demand response, peer-to-peer (P2P) energy trading, energy communities, optimization-based methodologies , advanced energy management models, transactive energy systems, and AI-driven energy market optimization
11. AI-based optimization of photovoltaic (PV) systems under high renewable penetration and energy community scenarios Equitable energy access, decarbonization, carbon footprint reduction with intelligent systems
12. Ethics, Policy, and Societal Impact of AI in Energy Responsible AI, inclusivity, and regulation in global energy transitions
Part IV – Case Studies and Future Directions
13. Case Studies: Global Perspectives on AI in Energy Real-world deployments from Asia, Africa, Europe, and the Americas
14. Future Trends and Challenges in AI for Energy Systems Digital twins, human-AI collaboration, emerging algorithms, advanced optimization techniques and next-generation energy management models and next-decade research agenda
1. Introduction: Artificial Intelligence for Next Generation Energy Systems Overview of AI techniques, energy transition challenges, digital transformation, and book roadmap
2. Machine Learning and Deep Learning in Energy Applications Fundamental algorithms, supervised/unsupervised learning, neural networks, reinforcement learning for forecasting and optimization
3. Big Data Analytics and Energy Intelligence Data-driven modeling, cloud and edge computing, handling high-dimensional datasets in energy systems
4. Quantum Computing for Future Energy Systems Role of quantum algorithms in optimization, simulation, and secure energy trading
Part II – AI in Energy Infrastructure
5. Smart Grids and Intelligent Distribution Systems AI for grid monitoring, dynamic pricing, fault detection, and grid automation
6. Renewable Energy Forecasting, PV System Optimization, and Integration in Smart Grids Solar/wind energy prediction models, hybrid approaches, uncertainty management in renewable-heavy grids including challenges of high renewable penetration and energy communities with distributed PV systems
7. AI for Energy Storage, Home Energy Management Systems, and Intelligent Control Intelligent charging/discharging strategies, HEMS, demand-side optimization, predictive maintenance, and energy resilience
8. IoT, Edge, and Cloud AI in Energy Systems Cyber-physical integration, real-time decision-making, digital twins for power systems
Part III – Security, Sustainability, and Society
9. Cybersecurity in AI-driven Energy Systems Threat modeling, anomaly detection, adversarial AI, and blockchain-based solutions
10. AI for Energy Market Optimization, Energy Communities, and Trading Bidding strategies, demand response, peer-to-peer (P2P) energy trading, energy communities, optimization-based methodologies , advanced energy management models, transactive energy systems, and AI-driven energy market optimization
11. AI-based optimization of photovoltaic (PV) systems under high renewable penetration and energy community scenarios Equitable energy access, decarbonization, carbon footprint reduction with intelligent systems
12. Ethics, Policy, and Societal Impact of AI in Energy Responsible AI, inclusivity, and regulation in global energy transitions
Part IV – Case Studies and Future Directions
13. Case Studies: Global Perspectives on AI in Energy Real-world deployments from Asia, Africa, Europe, and the Americas
14. Future Trends and Challenges in AI for Energy Systems Digital twins, human-AI collaboration, emerging algorithms, advanced optimization techniques and next-generation energy management models and next-decade research agenda
Product details
Product details
- Edition: 1
- Latest edition
- Published: May 1, 2027
- Language: English
About the editors
About the editors
FG
Fausto Pedro Garcia Marquez
Fausto Pedro García Márquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published numerous papers and books with international publishers of repute, and has been involved as a principal investigator in numerous international projects. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.
Affiliations and expertise
Professor, Universidad De Castilla-La Mancha, SpainMO
Mariya Ouaissa
Mariya Ouaissa is a Professor in Cybersecurity and Networks at Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech, Morocco. She received her PhD in Computer Science and Networks from ENSAM-Moulay Ismail University, Meknes, Morocco. She is a Co-Founder and IT Consultant at IT Support and Consulting Center. She also was a visiting professor at the School of Technology of Meknes Morocco. Dr. Ouaissa is member of the International Association of Engineers and International Association of Online Engineering. Her main research topics are IoT, M2M, D2D, WSN, Cellular Networks, and Vehicular Networks.
Affiliations and expertise
Assistant Professor, Cadi Ayyad University, Marrakech, MoroccoHS
Hemant Kumar Saini
Hemant Kumar Saini is an academic at the School of Computer Science & Engineering, Bennett University (The Times Group), Greater Noida, India, and at Lincoln University, Malaysia. His research interests include digital transformation technologies such as artificial intelligence (AI), quantum computing, the Internet of Things (IoT), blockchain, aerial vehicles, ad-hoc networks, digital twins, and edge and serverless computing, including cloud-native computing.
Affiliations and expertise
Academic, School of Computer Science and Engineering, Bennett University, Greater Noida, IndiaMO
Mariyam Ouaissa
Mariyam Ouaissa is currently an Assistant Professor in Networks and Systems at ENSA, Chouaib Doukkali University, El Jadida, Morocco. She received her Ph.D. from National Graduate School of Arts and Crafts, Meknes, Morocco and her Engineering Degree from National School of Applied Sciences, Khouribga, Morocco. Dr Ouaissa's research is multidisciplinary that focuses on Internet of Things, M2M, WSN, vehicular communications and cellular networks, security networks, congestion overload problem and the resource allocation management and access control. She is serving as a reviewer for international journals and conferences including as IEEE Access, Wireless Communications and Mobile Computing. She is also a member of "International Association of Engineers IAENG" and "International Association of Online Engineering", and she is an "ACM Professional Member".
Affiliations and expertise
Assistant Professor, ENSA, Chouaib Doukkali University, El Jadida, Morocco