Authors: T.S. Chung, T.W. Lau
Addresses: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. ' Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Abstract: In power system operation, dynamic economic dispatch (DED) represents a significant but complicated optimisation problem. Optimal dispatch signifies attractive economic returns in power system operation. Practically, the DED problem can involve real power limits, power balance, non-smooth fuel cost function as well as ramp rate limits. These involvements impose high complexity onto the solution of the problem. This paper presents a novel hybrid optimisation based on the particle swarm optimisation (PSO) and differential evolution (DE) algorithms to manage the DED. The hybrid approach (HPSO) incorporates DE operators into the PSO model to enrich the information exchanges amongst candidate solutions. A DED test system with smooth and non-smooth cost functions, 10-unit and 24-hour is quoted to demonstrate the effectiveness and feasibility of the proposed approach. Comparisons of results obtained with those reported highlight the promising capability of the proposed method.
Keywords: computational intelligence; power systems operation; dynamic economic dispatch; DED; hybrid optimisation; particle swarm optimisation; HPSO; differential evolution; non-smooth cost functions.
International Journal of Modelling, Identification and Control, 2009 Vol.8 No.4, pp.317 - 326
Available online: 09 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article