Research on Reactive Power Optimization Using Quantum Evolutionary Algorithm Based on NW Small World Model

doi:10.11930/j.issn.10.11930.2015.1.107

Abstract

Abstract: In view of the premature convergence problem of quantum evolutionary algorithm(QEA), a novel NW(Newman-Watts) small- world quantum evolutionary algorithm is proposed for reactive power optimization. This algorithm introduces the NW small world network model, and dynamically changes the neighborhood topology of each individual among population through a novel random adding edge method, which not only guarantees the diversity of evolution population, but also improves its balance capability of global exploration. Finally, the proposed algorithm is applied to address the reactive power optimization problem in IEEE 14-bus system and IEEE 30-bus system. The simulation analysis shows that the proposed NW small-world quantum evolutionary algorithm outperforms the standard QEA both in global search capability and convergence precision.

Key words: quantum evolution, NW small-world, neighborhood topology model, reactive power optimization

CLC Number:

TM721

MENG Anbo, YUE Longfei, XING Linhua, CHEN Yucheng, LI Yang. Research on Reactive Power Optimization Using Quantum Evolutionary Algorithm Based on NW Small World Model[J]. journal1, 2015, 48(1): 107-114.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.10.11930.2015.1.107

https://www.electricpower.com.cn/EN/Y2015/V48/I1/107

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