Title: A hybrid particle swarm optimisation with social weight for non-convex economic dispatch problem
Authors: Jinglei Guo; Zhijian Wu; Bin Zhao
Addresses: Department of Computer Science, Central China Normal University, Wuhan 430079, China ' State Key Lab of Software Engineering, Wuhan University, Wuhan 430072, China ' School of Automation, Wuhan University of Technology, Wuhan 430079, China
Abstract: This paper presents a hybrid particle swarm optimisation with social weight (HSWPSO) to solve the economic dispatch (ED) problem in power system. Due to equality constraints and non-convex characteristics in ED problem, HSWPSO employs social weight factor, extremum disturbance operator and correction operator to overcome difficulties. The social weight factor is used to improve the global and local search ability of the swarm. The extremum disturbance operator helps trapped particles escape from the local optima. The correction operator ensures the position of particle satisfy the power balance equation. HSWPSO algorithm is applied to two kinds of ED problems, namely ED with valve-point effects and ED with multiple fuels. Experiment results show the effectiveness and feasibility of HSWPSO.
Keywords: non-convex economic dispatch; particle swam optimisation; social weight factor; hybrid PSO; power systems; power balance equation; valve-point effects; multiple fuels.
International Journal of Computer Applications in Technology, 2013 Vol.46 No.3, pp.252 - 258
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 23 Mar 2013 *