Chapter

Advances in Neural Networks – ISNN 2009

Volume 5553 of the series Lecture Notes in Computer Science pp 152-161

Optimal Reactive Power Dispatch Using Particle Swarms Optimization Algorithm Based Pareto Optimal Set

  • Yan LiAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , Pan-pan JingAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , De-feng HuAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , Bu-han ZhangAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , Cheng-xiong MaoAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , Xin-bo RuanAffiliated withLancaster UniversityElectric Power Security and High Efficiency Lab, Huazhong University of Science and Technology
  • , Xiao-yang MiaoAffiliated withCarnegie Mellon UniversityXinxiang Electric Power Supply Corporation of Henan Electric Power Company
  • , De-feng ChangAffiliated withCarnegie Mellon UniversityXinxiang Electric Power Supply Corporation of Henan Electric Power Company

* Final gross prices may vary according to local VAT.

Get Access

Abstract

An improved particle swarms optimization algorithm based on Pareto Optimal set is proposed to optimize the reactive power in power system, which is a multiple objectives optimization problem. The proposed algorithm develops the new fitness assignment and random inertia weight strategy, problem-specific linkages can be learned by examining a randomly chosen collection of points in the search space, the improved algorithm also has the ability to avoid getting trapped in local optima due to prematurity, applying it to the calculation of the power systems of IEEE6-bus and IEEE14-bus, the calculation results prove its effectiveness.

Keywords

Reactive power optimization Pareto Optimal set Fitness assignment Random inertia weight strategy