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Multi-Objective Coordinated Optimization Method of Active and Reactive Power Considering Power Characteristics of Renewable Energy Converters

Author

Listed:
  • Xuebin Wang

    (State Grid Qinghai Electric Power Company Electric Power Research Institute, Xining 810000, China
    State Grid Qinghai Electric Power Company, Xining 810000, China)

  • Guobin Fu

    (State Grid Qinghai Electric Power Company Electric Power Research Institute, Xining 810000, China
    State Grid Qinghai Electric Power Company, Xining 810000, China)

  • Yanbo Chen

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102200, China)

  • Rui Song

    (State Grid Qinghai Electric Power Company Electric Power Research Institute, Xining 810000, China
    State Grid Qinghai Electric Power Company, Xining 810000, China)

  • Haibin Sun

    (State Grid Qinghai Electric Power Company Electric Power Research Institute, Xining 810000, China
    State Grid Qinghai Electric Power Company, Xining 810000, China)

  • Jiahao Ma

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102200, China)

  • Tao Huang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102200, China)

Abstract

In new power systems with a high proportion of renewable energy, optimization criteria based solely on economic efficiency or system stability may lead to a reduction in the static stability domain of the system or lead to long-term deviations from economic operation, thus reducing the overall applicability of such methods. This paper proposes a multi-objective active–reactive power coordinated optimization model that considers both economic efficiency and static stability indicators. The goal of the model is to minimize operating costs while optimizing static stability margins. It combines the reactive power support capabilities of converters and other reactive power compensation equipment to ensure safe and economical dispatch of the system. The proposed method is verified through a case study, which shows that this method can make full use of the potential reactive power regulation capability of the converter. At the same time, the economics and stability of the system are significantly improved by using this method. The overall improvement is about is 12.3%.

Suggested Citation

  • Xuebin Wang & Guobin Fu & Yanbo Chen & Rui Song & Haibin Sun & Jiahao Ma & Tao Huang, 2024. "Multi-Objective Coordinated Optimization Method of Active and Reactive Power Considering Power Characteristics of Renewable Energy Converters," Energies, MDPI, vol. 17(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:24:p:6370-:d:1546756
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    References listed on IDEAS

    as
    1. Hu, Shu-bo & Gao, Zheng-nan & He, Hai & Cao, Wen-ping & Zhao, Yu-ting & Zhou, Wei & Gu, Hong & Sun, Hui, 2020. "Adaptive time division power dispatch based on numerical characteristics of net loads," Energy, Elsevier, vol. 205(C).
    2. Li, Yang & Han, Meng & Shahidehpour, Mohammad & Li, Jiazheng & Long, Chao, 2023. "Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response," Applied Energy, Elsevier, vol. 335(C).
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