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Optimal Power Flow Using Gbest-Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule

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  • Gonggui Chen
  • Siyuan Qiu
  • Zhizhong Zhang
  • Zhi Sun
  • Honghua Liao

Abstract

The optimal power flow (OPF) is well-known as a significant optimization tool for the security and economic operation of power system, and OPF problem is a complex nonlinear, nondifferentiable programming problem. Thus this paper proposes a Gbest-guided cuckoo search algorithm with the feedback control strategy and constraint domination rule which is named as FCGCS algorithm for solving OPF problem and getting optimal solution. This FCGCS algorithm is guided by the global best solution for strengthening exploitation ability. Feedback control strategy is devised to dynamically regulate the control parameters according to actual and specific feedback value in the simulation process. And the constraint domination rule can efficiently handle inequality constraints on state variables, which is superior to traditional penalty function method. The performance of FCGCS algorithm is tested and validated on the IEEE 30-bus and IEEE 57-bus example systems, and simulation results are compared with different methods obtained from other literatures recently. The comparison results indicate that FCGCS algorithm can provide high-quality feasible solutions for different OPF problems.

Suggested Citation

  • Gonggui Chen & Siyuan Qiu & Zhizhong Zhang & Zhi Sun & Honghua Liao, 2017. "Optimal Power Flow Using Gbest-Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-14, December.
  • Handle: RePEc:hin:jnlmpe:9067520
    DOI: 10.1155/2017/9067520
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    Cited by:

    1. Gang Yao & Rui Li & Yang Yang, 2023. "An Improved Multi-Objective Optimization and Decision-Making Method on Construction Sites Layout of Prefabricated Buildings," Sustainability, MDPI, vol. 15(7), pages 1-23, April.

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