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Multi-Objective Optimization Operation of Multi-Agent Active Distribution Network Based on Analytical Target Cascading Method

Author

Listed:
  • Yiran Zhao

    (State Grid Henan Electric Power Company Xixia County Power Supply Company, Nanyang 474500, China)

  • Yong Xue

    (State Grid Henan Electric Power Company Xixia County Power Supply Company, Nanyang 474500, China)

  • Ruixin Zhang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Jiahao Yin

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Yang Yang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

  • Yanbo Chen

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China)

Abstract

In the context of the green energy transition, the rapid expansion of flexible resources such as distributed renewable energy, electric vehicles (EVs), and energy storage has significantly impacted the operation of distribution networks. This paper proposes a multi-objective optimization approach for active distribution networks (ADNs) based on analytical target cascading (ATC). Firstly, a dynamic optimal power flow (DOPF) calculation method is developed using second-order conic relaxation (SOCR) to address power flow and voltage issues in the distribution network, incorporating active management (AM) elements. Secondly, this study focuses on aggregating the power of flexible resources within station areas connected to distribution network nodes and incorporating these resources into demand response (DR) programs. Finally, a two-layer model for collaborative multi-objective scheduling between station areas and the active distribution network is implemented using the ATC method. Case studies demonstrate the model’s effectiveness and validity, showing its potential for enhancing the operation of distribution networks amidst the increasing integration of flexible resources.

Suggested Citation

  • Yiran Zhao & Yong Xue & Ruixin Zhang & Jiahao Yin & Yang Yang & Yanbo Chen, 2024. "Multi-Objective Optimization Operation of Multi-Agent Active Distribution Network Based on Analytical Target Cascading Method," Energies, MDPI, vol. 17(20), pages 1-26, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5022-:d:1495366
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