A hybrid genetic algorithm-interior point method for optimal reactive power flow

Wei Yan, Fang Liu, C. Y. Chung, K. P. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

158 Citations (Scopus)

Abstract

By integrating a genetic algorithm (GA) with a nonlinear interior point method (IPM), a novel hybrid method for the optimal reactive power flow (ORPF) problem is proposed in this paper. The proposed method can be mainly divided into two parts. The first part is to solve the ORPF with the IPM by relaxing the discrete variables. The second part is to decompose the original ORPF into two sub-problems: continuous optimization and discrete optimization. The GA is used to solve the discrete optimization with the continuous variables being fixed, whereas the IPM solves the continuous optimization with the discrete variables being constant. The optimal solution can be obtained by solving the two sub-problems alternately. A dynamic adjustment strategy is also proposed to make the GA and the IPM to complement each other and to enhance the efficiency of the hybrid proposed method. Numerical simulations on the IEEE 30-bus, IEEE 118-bus and Chongqing 161-bus test systems illustrate that the proposed hybrid method is efficient for the ORPF problem.

Original languageEnglish
Pages (from-to)1163-1169
Number of pages7
JournalIEEE Transactions on Power Systems
Volume21
Issue number3
DOIs
Publication statusPublished - Aug 2006

Keywords

  • Genetic algorithm (GA)
  • Interior point method (IPM)
  • Nonlinear programming
  • Optimal reactive power flow (ORPF)

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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