Advances In Ai For Simulation And Optimization Of Energy Systems

Description

Edited by Al-Haija, Qasem Abu; Edited by Mohamed, Omar; Edited by Elhaija, Wejdan Abu

Short /annotation:

Advances in AI for the Simulation and Optimization of Energy Systems explore AI”s groundbreaking role in the future of energy. Bringing together leading researchers and practitioners in AI and energy systems, this book is an invaluable resource for professionals who want to stay ahead of the curve in this rapidly evolving field.

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Advances in AI for Simulation and Optimization of Energy Systems explores AI’s groundbreaking role in the future of energy. As the demand for cleaner, more efficient energy systems grows, AI‑driven methodologies are leading the way in simulating and optimizing critical processes across the power generation, transmission, and storage sectors. Whether applied to traditional power grids, renewable energy systems, or energy markets, AI techniques such as neural networks, reinforcement learning, fuzzy logic, and metaheuristic optimization are revolutionizing how energy systems are modeled and managed.

This comprehensive volume offers:

• In‑depth chapters on AI‑driven simulation and optimization strategies
• Case studies that demonstrate real‑world applications of AI in energy systems
• An examination of the ethical concerns and legal frameworks surrounding AI
• Cutting‑edge methodologies for improving energy technologies’ accuracy, efficiency, and performance

Bringing together leading researchers and practitioners in AI and energy systems, this book is an invaluable resource for academics, engineers, and professionals who want to stay ahead of the curve in this rapidly evolving field.

Table of contents:

1. Fundamentals of Machine Learning Models 2. Applications of Artificial Intelligence Techniques in Power Systems 3. Applications of Artificial Intelligence Techniques in Hybrid Renewable Energy Systems 4. Applications of Artificial Intelligence Techniques in Smart Grid Systems 5. Algae-Based Carbon Sequestration: Optimizing Renewable Energy and Climate Strategy 6. The Use of BWO for Calibration of LFC of a Multi-Area Power System with Real-Life Wind Energy Penetration 7. Advanced Biofuel Generations: Optimizing Sustainable Agriculture and Renewable Energy Transition 8. Hierarchical Robust Optimization of Chemical Processes and Energy Systems Through In-Depth Industrial Data Analysis and Machine Learning 9. Ethical and Legal Aspects of Machine Learning in 5G-Enabled Smart City and Energy Grid Cyber-Defence

Biographical note:

Qasem Abu Al‑Haija received his Ph.D. from Tennessee State University (TSU), USA, in 2020. He is an assistant professor in the Department of Cybersecurity, Faculty of Computer & Information Technology, Jordan University of Science and Technology, Irbid, Jordan. He authorizes more than 250 scientific research papers and book chapters. His research interests include artificial intelligence (AI), cybersecurity and cryptography, the Internet of Things (IoT), cyber‑physical systems (CPS), time series analysis (TSA), and computer arithmetic. Recently, he was listed as one of the world’s top 2% of scientists, and his list was released publicly by Stanford University and other publishing houses.

Omar Mohamed earned his Ph.D. in Electrical Engineering in 2012 from the University of Birmingham, England. He received his B.Sc. and M.Sc. degrees in Electrical Engineering with honors from the University of Garyounis (current name: University of Benghazi), Libya, in 2008 and 2005, respectively. He worked as a lecturer and held some administrative positions at the University of Garyounis. In September 2015, he joined Princess Sumaya University for Technology (PSUT), King Abdullah II School of Engineering, Department of Electrical Engineering as an assistant professor and was promoted to associat