Advances in AI for Simulation and Optimization of Energy Systems (eBook, PDF)

Redaktion: Al-Haija, Qasem Abu; Elhaija, Wejdan Abu; Mohamed, Omar

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 195
• Erscheinungstermin: 20. März 2025
• Englisch
• ISBN-13: 9781040315293
• Artikelnr.: 72836949

Autorenporträt

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 associate professor in December 2020. Her Royal Highness Princess Sumaya Bint Al¿Hassan awarded him the distinguished teacher award in 2019. He is an associate professor at Libyan International Medical University (LIMU). His area of interest is modeling and control of power generation plants. Wejdan Abu Elhaija is a professor of Electrical Engineering/Electrical Machines. She is HRH's Advisor for Academic Affairs at the Royal Scientific Society (RSS) and the President of Princess Sumaya University for Technology (PSUT) in Jordan. She held some administrative posts, including Vice President for Al¿Zaytoonah University of Jordan in 2016. When she was named Dean of the King Abdullah II School of Engineering at Princess Sumaya University of Technology in 2011, she became Jordan's first female Dean of Engineering (PSUT). She earned her Ph.D. in Electrical Engineering from Queen's University Belfast in the United Kingdom. Her work received numerous honors, including the Hisham Adeeb Hijjawi Applied Science Award in 2004, the King Abdullah II Design and Development Bureau Award for Best Design Model in 2008, and the Jordan University Center for Women's Studies Award in 2007. In 2007, she was appointed President's Assistant for Quality Assurance, and in 2009, she was appointed Head of the Electronics Engineering Department. In 2012, the IEEE presented her with a Clementina Saduwa Award for Region 8 for her remarkable contribution to engineering and IT. She was honored by the US State Department's Women in Science Hall of Fame in 2012. The Senate of Queen's University Belfast, Northern Ireland, awarded her a Doctor of Science in Engineering (DSc) [honoris causa] degree in early 2013 for her significant contributions to engineering. She is a fellow of the British Higher Education Academy in teaching and learning, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a consulting engineer at the Jordanian Engineers Association, a member of the Scientific Committee for the InterAcademy Partnership (IAP) as a representative of the Royal Scientific Society of Jordan, and a member of the Science Education Committee at the Association of Academies and Societies of Science in Asia (AASSA). In 2021, she was appointed to represent the IEEE International Society as an ABET Evaluator. She was named editor-in-chief of the Jordanian Journal of Computers and Information Technology in 2022. (JJCIT). She was nominated to join the International Women's Forum - Jordan Chapter in 2022. Her research has been published in numerous peer¿reviewed and highly indexed journals.

Inhaltsangabe

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