A hybrid particle swarm optimisation with social weight for non-convex economic dispatch problem

Authors:
Jinglei Guo;Zhijian Wu;Bin Zhao
Affiliations:
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
Venue:
International Journal of Computer Applications in Technology
Year:
2013

Citing 4
Cited 0

Identification for fractional order rational models based on particle swarm optimisation

International Journal of Computer Applications in Technology
On the optimal size of a robust swarm

International Journal of Computer Applications in Technology
Particle swarm optimisation of a discontinuous control for a wheeled mobile robot with two trailers

International Journal of Computer Applications in Technology
Evolutionary programming techniques for economic load dispatch

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

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.