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The Key Research and Application in Grid Planning Using Improved Genetic Algorithm

Author

Listed:
  • Fan Yina

    (Beijing Normal University, Zhuhai, China)

  • Lang Zixi

    (South China University of Technology, Guangzhou, China)

  • Ren Yuan

    (Shanghai Dianji University, Shanghai, China)

  • Dong Ruiwen

    (Beijing Normal University, Zhuhai, China)

Abstract

In order to guarantee the power grid operation under the premise of reliability and stability, acquire relative economic investment and operating cost, and adaptable to all kinds of change flexibly, this article improves the traditional generic algorithm by considering the various objective function and constraint condition. The improved algorithm can search and optimize according to mechanism for the survival of the fittest. It is especially suited for the optimization solution of integer variables. The application of the algorithm proposed to fifteen nodes system of a certain city and comparative experiments show that the algorithm has fast convergence speed and optimizing result. A comparative analysis of the optimizing project using improved generic algorithm and computational result using engineering computational method in practical grid planning yield the same results, this shows that the improved algorithm has better adaptability.

Suggested Citation

  • Fan Yina & Lang Zixi & Ren Yuan & Dong Ruiwen, 2019. "The Key Research and Application in Grid Planning Using Improved Genetic Algorithm," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 10(3), pages 59-75, July.
    • Handle: RePEc:igg:joris0:v:10:y:2019:i:3:p:59-75
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