Day-Ahead Optimal Scheduling of Distributed Resources and Network Reconfiguration Under Uncertain Environment

Abstract

Future distribution systems can be seen with very high penetration of renewable energy sources (RESs) such as solar photovoltaics and wind turbines on account of diverse techno-economic and social concerns. The uncertainty and variability associated with these RESs along with the stochastic nature of load demand imposes real challenges to system operators. More realistic formulations and suitably tailored methodologies can coordinate well-known operational strategies to achieve optimum performance of distribution systems. This article presents a new methodology to optimally coordinate day-ahead scheduling of distributed resources (DRs) with distribution network reconfiguration (DNR). The scheduling problem optimizes economic operation by considering O&M charges of DRs, emission charges of micro turbines, and sale/purchase of electricity to the customers/grid whereas feeder power losses are minimized by solving DNR problem. Proposed methodology coordinates these two key strategies by coarse and fine tuning to optimize several techno-economic and social objectives while duly addressing more realistic scenario of distribution systems. Application results on a modified standard 33-bus distribution system demonstrate the effectiveness of the proposed methodology.

Keywords:

• day-ahead operation
• distributed resources
• microgrids
• network reconfiguration
• uncertainty model

Additional information

Notes on contributors

Neeraj Kanwar

Neeraj Kanwar completed B.E. in Electrical Engineering from Rajasthan University, Jaipur, India, in 2005. She received the M. Tech. in Power Systems from Malaviya National Institute of Technology, Jaipur, India, in 2010. She has completed Ph.D. from the same institute in 2017. She is presently working as an Assistant Professor (Selection grade) in the Department of Electrical Engineering, Manipal University Jaipur, India. Her research interests are renewable energy sources, smart grid, network reconfiguration (NR), distributed generations (DGs), power system operation and planning, bio-inspired and swarm-based optimization techniques, application of optimization techniques in power system.

Nikhil Gupta

Nikhil Gupta has more than 33 years of teaching, research and industrial experience. He received M. Tech. and Ph.D. in electrical engineering from Malaviya National Institute of Technology, Jaipur, India, in 2006 and 2012, respectively. He is presently working as an Associate Professor in Malaviya National Institute of Technology, Jaipur, India. He has published more than 120 papers in journals and conferences and has supervised several Ph.D. and Master’s students. His research interests include Planning and operation of distribution systems, distributed energy resources, economic operation and artificial intelligence.

Khaleequr Rehman Niazi

Khaleequr Rehman Niazi has more than 33 years of teaching and research experience. He is currently a Professor (HAG) in the Department of Electrical Engineering and Registrar, Malaviya National Institute of Technology, Jaipur, India. He has published more than 200 papers in journals and conferences and has supervised several Ph.D. and Master’s students. His research interests include conventional power and renewable energy systems, including power system stability, distribution network reconfiguration, flexible alternating current transmission systems, and application of AI and artificial neural network techniques to power systems.

Anil Swarnkar

Anil Swarnkar has more than 25 years of teaching, research and industrial experience. He received M. Tech. and Ph.D. in electrical engineering from Malaviya National Institute of Technology (MNIT), Jaipur, India, in 2005 and 2012, respectively. He is currently working as an Associate Professor in Malaviya National Institute of Technology, Jaipur, India. He has published more than 100 papers in journals and conferences and has supervised several Ph.D. and Master’s students. His research interests include operation and control of power systems and AI- techniques.

Almoataz Y. Abdelaziz

Almoataz Y. Abdelaziz received the Ph.D. degree in electrical engineering according to the channel system between Ain Shams University, Egypt, and Brunel University, U.K., in 1996. He is currently professor of electrical power engineering with Ain Shams University, since 2007. He was the Vice Dean for Education and Students Affairs in Faculty of Engineering and Technology, Future University in Egypt from 2018-2019. He has authored or coauthored more than 450 refereed journal and conference papers, 30 book chapters, and five edited books with Elsevier and Springer. He is an editor of Electric Power Components and Systems journal, an Editorial Board member, an Editor, an Associate Editor, and an Editorial Advisory Board member for many international journals. His research areas include the applications of artificial intelligence, evolutionary and heuristic optimization techniques to power system planning, operation, and control.