The book is dedicated to the implementation of different multi-criteria decision-making techniques for various problems concerning planning and operation of the smart grid from the Society 5.0 perspective. It consists of a practical explanation of several multi-criteria approaches and examples of their application to real problems. In this book, the choice of the optimal smart grid strategy in planning and operation is made. Various areas of smart grid problems are analyzed, from the smart grid project efficiency assessment to the electric vehicle charging schedule optimization. The comparison of alternatives is made using different techniques taking into account the presence of multiple criteria of both qualitative and quantitative nature, different performance indicators, and the uncertain environment of the smart grid.

The book outlines in clear terms how the electricity grid can be modernized in such a way that it monitors, protects, and automatically optimizes the operation of its interconnected elements, taking into account different stakeholders and criteria and society in general. The book covers various smart grid aspects-from the distributed generator through the medium-voltage network and distribution system, to energy storage installations and to end-use consumers and their thermostats, electric vehicles, appliances, and other household devices. The book serves as a practical guide for researchers, energy and utility professionals, power system planners, regulators, policymakers, and others in the field.

Auteur

Dr. Lazar Z. Velimirovic received his M.S. and Ph.D. degrees in Electrical Engineering from the Faculty of Electronic Engineering, University of Nis, Serbia, in 2008 and 2013, respectively. Since 2011, he has been with the Mathematical Institute of the Serbian Academy of Sciences and Arts, Belgrade, Serbia, where he is now a senior research associate. He was a project leader of more international and national projects. Since 2017, he has been a chairman of the seminar called decision making-theory, technology, and practice. He is a member of the IEEE. Dr. Velimirovic is the author or co-author of more than 75 scientific publications in international journals and conferences. He has been a program and organizing committee member of more international conferences. His main research interests include signal processing, optimization, decision-making theory, distribution systems planning, distribution management systems, and machine learning.Dr. Aleksandar Janjic graduated in 1989 from the University of Belgrade, Serbia. He received his Ph.D. degree from the Faculty of Technical Sciences, University of Novi Sad, in 2007. After more than 20-year-long experience in the power industry, in 2011 he is with the Faculty of Electronic Engineering, University of Nis, Serbia, giving lectures on the subjects of distribution system planning and distributed generation. His areas of expertise are power distribution system planning and decision-making in power systems. He is the author or co-author of over 100 scientific papers from the fields of expertise and more than 70 publications in international journals and conferences. Dr. Janjic is the chairman of the planning session of the CIRED National Committee. He is a member of the Power & Energy Society (PES) of the Institute of Electrical and Electronic Engineers (IEEE) and the member of the Serbian engineering chamber.

Jelena D. Velimirovic is currently a Research Assistant at the Mathematical Institute of the Serbian Academy of Sciences and Arts and a Ph.D. candidate at the Technical Faculty in Bor, University of Belgrade. She received her M.S. in Emergency Management from the Faculty of Occupational Safety, University of Nis, Serbia, in 2014. She was a team member of more international and national projects and an organizing committee member of several international conferences. She is the author or co-author of more than 30 scientific publications in international journals and conferences. Her main research interests include engineering management, decision-making theory, risk analysis, and optimization.