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Cluster Partition Method of Large-Scale Grid-Connected Distributed Generations considering Expanded Dynamic Time Scenarios

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  • Chang Ye
  • Kan Cao
  • Haiteng Han
  • Ziwen Liu
  • Defu Cai
  • Dan Liu
  • Dazhong Ma

Abstract

The reasonable clustering of large-scale distributed generations (DGs) can optimize the scheduling control and operation monitoring of the power grid, which ensures the orderly and efficient integration of DGs into the power system. In this article, the influence of internal and external flexible resources is considered in the DG cluster partition, and the comprehensive performance indexes with expanded dynamic time scenario are proposed to realize the dynamic cluster partition. Firstly, the active and reactive power balance indexes considering the flexible resources are derived, which forms the comprehensive index together with the structure index. Then, the comprehensive index is expanded to the dynamic forms, which reflects the real-time cluster performance, and the cluster partition method is given with the genetic algorithm. Finally, the effectiveness verification of the proposed cluster partition method is carried out with the 14- and 33-bus systems.

Suggested Citation

  • Chang Ye & Kan Cao & Haiteng Han & Ziwen Liu & Defu Cai & Dan Liu & Dazhong Ma, 2022. "Cluster Partition Method of Large-Scale Grid-Connected Distributed Generations considering Expanded Dynamic Time Scenarios," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, February.
    • Handle: RePEc:hin:jnlmpe:1934992
    DOI: 10.1155/2022/1934992
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    Cited by:

    1. Hongwei Li & Qing Xu & Shitao Wang & Huihui Song, 2022. "Peak Shaving Methods of Distributed Generation Clusters Using Dynamic Evaluation and Self-Renewal Mechanism," Energies, MDPI, vol. 15(19), pages 1-17, September.

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