Dynamic Multi-Groups Self-Adaptive Differential Evolution Algorithm with Local Search for Reactive Power Optimization

Author

Zhang, Xuexia ; Chen, Weirong ; Cai, Wenzhao ; Dai, Chaohua

Author_Institution

Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu

fYear

2009

fDate

27-31 March 2009

Firstpage

1

Lastpage

4

Abstract

This paper proposes a novel algorithm, dynamic multi- groups self-adaptive differential evolution with local search (DMSDELS), for reactive power optimization of power system. The objective of optimization is minimizing active power losses in transmission network while maintaining the quality of voltages. The new method is tested on IEEE 118-Bus power system. The numerical results, compared with other stochastic search algorithms, show that DMSDELS could find high-quality solutions with more reliability and efficiency.

Keywords

evolutionary computation; power supply quality; reactive power; transmission networks; IEEE 118-Bus power system; active power losses; dynamic multigroup self-adaptive differential evolution algorithm; local search; numerical results; power system; reactive power optimization; stochastic search algorithms; transmission network; voltage quality; Acceleration; Chromium; Genetic mutations; Heuristic algorithms; Maintenance; Power system dynamics; Power system reliability; Power system simulation; Reactive power; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific

Conference_Location

Wuhan

Print_ISBN

978-1-4244-2486-3

Electronic_ISBN

978-1-4244-2487-0

Type

conf

DOI

10.1109/APPEEC.2009.4918302

Filename

4918302