Social Cognitive Optimization Algorithm with Reactive Power Optimization of Power System

Author

Wei, Zhanhong ; Cui, Zhihua ; Zeng, Jianchao

Author_Institution

Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China

fYear

2010

fDate

26-28 Sept. 2010

Firstpage

11

Lastpage

14

Abstract

A reactive power optimization is a multi-modal, mixed-variable, multi-constraint and nonlinear planning problem. In the last decades, many computational intelligence-based techniques have been proposed for reactive power optimization problem, such as genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), Tabu search. Recently, a new swarm intelligent algorithm, social cognitive optimization algorithm (SCOA), is proposed by simulating the human competition process. In this paper, it is introduced to solve reactive power problem. Two famous examples: IEEE-57bus and IEEE-118bus system are used to test, simulation results show SCOA is effective.

Keywords

genetic algorithms; particle swarm optimisation; power system planning; reactive power; search problems; IEEE- 57 bus; IEEE-118 bus; SCOA; differential evolution; genetic algorithm; particle swarm optimization; power system nonlinear planning problem; reactive power optimization; social cognitive optimization algorithm; swarm intelligent algorithm; tabu search; Biological system modeling; Indexes; Optimization; Particle swarm optimization; Reactive power; Voltage control; Social cognitive optimization algorithm; reactive power optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Aspects of Social Networks (CASoN), 2010 International Conference on

Conference_Location

Taiyuan

Print_ISBN

978-1-4244-8785-1

Type

conf

DOI

10.1109/CASoN.2010.10

Filename

5636861