Predictive Modelling for Energy Management and Power Systems Engineering

Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets.

Professor Ravinesh Deo is an Associate Professor at University of Southern Queensland, Australia, Program Director for Postgraduate Science Program and Research Leader in Artificial Intelligence. He also serves as Associate Editor for two international journals: Stochastic Environmental Research and Risk Assessment and the ASCE Journal Hydrologic Engineering journal (USA). As an Applied Data Scientist with proven leadership in artificial intelligence, his research develops decision-systems with machine learning, heuristic and metaheuristic algorithms to improve real-life predictive systems especially using deep learning explainable AI, convolutional neural networks and long short-term memory networks. He was awarded internationally competitive fellowships including Queensland Government U.S. Smithsonian Fellowship, Australia-India Strategic Fellowship, Australia-China Young Scientist Exchange Award, Japan Society for Promotion of Science Fellowship, Chinese Academy of Science Presidential International Fellowship and Endeavour Fellowship. He is a member of scientific bodies, won Publication Excellence Awards, Head of Department Research Award, Dean’s Commendation for Postgraduate Supervision, BSc Gold Medal for Academic Excellence and he was the Dux of Fiji in Year 13 examinations. Professor Deo held visiting positions at United States Tropical Research Institute, Chinese Academy of Science, Peking University, Northwest Normal University, University of Tokyo, Kyoto and Kyushu University, University of Alcala Spain, McGill University and National University of Singapore. He has undertaken knowledge exchange programs in Singapore, Japan, Europe, China, USA and Canada and secured international standing by researching innovative problems with global researchers. He has published Books with Springer Nature, Elsevier and IGI and over 190 publications of which over 140 are Q1 including refereed conferences, Edited Books and book chapters. Professor Deo’s papers have been cited over 4,000 times with Google Scholar H-Index of 36 and a Field Weighted Citation Index exceeding 3.5. Dr. Pijush Samui is an Associate Professor, in the Department of Civil Engineering, at NIT Patna, India, and an Adjunct Professor at Ton Duc Thang University in Ho Chi Minh City, Vietnam. He received his PhD in Geotechnical Engineering from the Indian Institute of Science Bangalore in 2008. His research interests include geohazards; earthquake geotechnical engineering; concrete technology, pile foundation and slope stability and application of AI in civil engineering. He has published more than 21 books, 32 book chapters and over 200 research papers in high impact factor journals as well as 30 conference proceedings. Sanjiban Sekhar Roy is an Associate Professor in the School of Computer Science and Engineering, Vellore Institute of Technology. He joined VIT in the year 2009 as an Asst. Professor. His research interests include Deep Learning and advanced machine learning. He has