Improved Real-Coded Genetic Algorithm for Fixed Head Hydrothermal Power System

Abstract

This article proposes and suggested improves real-coded genetic algorithm (IRCGA) for optimal scheduling of thermal plants in coordination with fixed head hydro units. Genetic algorithm (GA) is based on inbred operation of human chromosomes. GA has the ability to establish the global or very close to the global optima. Here, in this article to heighten convergence speed and solution quality the IRCGA method has been recommended. Two different test systems have been used here to verify the effectiveness of the proposed IRCGA method. The results obtained from the emerged IRCGA method have been compared with other evolutionary techniques. The simulation results from different test systems demonstrate that the proposed IRCGA algorithm has the capability to generate better result.

Keywords:

• Constraint handling
• Fixed head
• Hydrothermal system
• Improved real-coded genetic algorithm
• Penalty function

Additional information

Notes on contributors

Jagat Kishore Pattanaik

Jagat Kishore Pattanaik received both the ME and PhD degrees in electrical engineering from Jadavpur University, Kolkata, India. His research interests are soft computing application in optimization of modern power system and power quality. He has published several research papers in reputed international journals and conferences.

Mousumi Basu

Mousumi Basu received the PhD degree from Jadavpur University, Kolkata, India. She is currently working as a professor in the Department of Power Engineering, Jadavpur University. She has a vast teaching experience and several reputed publications in international journals and conferences to her credit. Her research interests are power system optimization and soft computing technique. Email: [email protected]

Deba Prasad Dash

Deba Prasad Dash received the PhD degree from Jadavpur University, Kolkata, India. He is currently working as an associate professor in the Department of Electrical Engineering, Government College of Engineering, Kalahandi, Odisha, India. He has more than 15 years of teaching experience and his research interests are evolutionary computing techniques and its application to power system planning, operation and control. Email: [email protected]