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Information Technology Journal
  Year: 2010 | Volume: 9 | Issue: 4 | Page No.: 749-757
DOI: 10.3923/itj.2010.749.757
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Improved Strength Pareto Evolutionary Algorithm with Local Search Strategies for Optimal Reactive Power Flow

Li Zhihuan, Li Yinhong and Duan Xianzhong

In this study, several versions of Strength Pareto Evolutionary Algorithm (SPEA, SPEA2 and SPEA2+) are adopted and improved for voltage/reactive power control and simultaneously loss reduction in Optimal Reactive Power Flow (ORPF) of power systems. The purpose of ORPF is to provide a solution that minimizes real power loss and improves voltage profile by determining generator voltages, reactive power support of shunt capacitors and tap changing transformers. To enhance the algorithm’s exploiting capability, several problem-specific Local Search Strategies (LSSs) are incorporated to formulate three improved versions of SPEA (ISPEA, ISPEA2 and ISPEA2+). A comparative study between original SPEAs and improved SPEAs is also performed for ORPF on standard New England 39-bus test system. Pareto fronts and outer solutions achieved are compared and their nondominated sets are also analyzed using C measure. Experimental results validated the effectiveness of SPEA2+ and also demonstrated the further performance improvement in ISPEA2+ with LSSs. ISPEA2+ was found to be one of the efficient potential candidates in solving power system multiobjective optimization problems.
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How to cite this article:

Li Zhihuan, Li Yinhong and Duan Xianzhong, 2010. Improved Strength Pareto Evolutionary Algorithm with Local Search Strategies for Optimal Reactive Power Flow. Information Technology Journal, 9: 749-757.

DOI: 10.3923/itj.2010.749.757


28 October, 2016
Great contribution




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