Non-dominated Sorting Disruption-based Gravitational Search Algorithm with Mutation Scheme for Multi-objective Short-Term Hydrothermal Scheduling

Abstract

The short-term economical/environmental hydrothermal scheduling problem is formulated as a non-linear and non-convex constrained multi-objective optimization problem considering transmission losses and valve point loading effects. This article presents a non-dominated sorting disruption-based gravitational search algorithm with mutation to solve fixed-head and variable-head short-term economical/environmental hydrothermal scheduling problems. In this solution technique, a set of non-dominated solutions are obtained by using the concept of non-dominated sorting and an external archive. Thereafter, a fuzzy decision-making approach has been applied to achieve a suitable and the best compromising solution from the non-dominated solution set. Finally, the non-dominated sorting disruption-based gravitational search algorithm with mutation approach is demonstrated on three test systems: fixed-head two hydro and two thermal plants, two hydro and four thermal plants, and variable-head cascaded four hydro and three thermal plants. Simulation results obtained from this approach are compared with the other methods reported in the literature and it has been found that the proposed approach yields better solutions and is efficient for solving short-term economical/environmental hydrothermal scheduling problems.

Keywords:

• hydrothermal system
• multi-objective optimization
• non-dominated sorting
• disruption-based gravitational search algorithm
• sign and reordering mutations

Additional information

Notes on contributors

Gouthamkumar Nadakuditi

Gouthamkumar Nadakuditi received his B.Tech. in electrical and electronics engineering from Lakireddy Bali Reddy College of Engineering (LBRCE), Mylavaram, Andhra Pradesh, India, in 2009 and his M.Tech. in electrical engineering from the National Institute of Technology, Hamirpur, Himachal Pradesh, India, in 2012. He is currently working as a full-time Ph.D. research scholar in the Department of Electrical Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh, India. His primary research focuses on single-objective, multi-objective, and stochastic multi-objective short-term hydrothermal generation scheduling.

Veena Sharma

Veena Sharma received her B.Tech. in electrical engineering from Regional Engineering College (REC) Hamirpur, Himachal Pradesh, India, in 1990; her M.Tech. in instrumentation and control engineering from Punjab Agricultural University Ludhiana, India, in 1993; and her Ph.D. from Punjab Technical University, Jalandhar, in 2006. She is currently working as an associate professor in the Electrical Engineering Department (EED), National Institute of Technology, Hamirpur, Himachal Pradesh, India. Her research interests include power system optimization, power generation, operation, and control.

Ram Naresh

Ram Naresh received his B.E. in electrical engineering in 1987; his M.E. in power systems from Punjab Engineering College, Chandigarh, in 1990; and his Ph.D. from University of Roorkee, India, in 1999. He joined REC, Hamirpur, in 1989. He is currently working as a professor in EED, National Institute of Technology, Hamirpur, Himachal Pradesh, India. He has published a number of research articles in national and international journals and has provided consultancy services to the electric power industry. His research interests are artificial intelligence applications to power system optimization problems, evolutionary computation, neural networks, and fuzzy systems.