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Flexibility-Oriented AC/DC Hybrid Grid Optimization Using Distributionally Robust Chance-Constrained Method

Author

Listed:
  • Yue Chen

    (Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China)

  • Qiuyu Lu

    (Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China)

  • Kaiyue Zeng

    (Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China)

  • Yinguo Yang

    (Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China)

  • Pingping Xie

    (Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China)

Abstract

With the increasing integration of stochastic sources and loads, ensuring the flexibility of AC/DC hybrid distribution networks has become a pressing challenge. This paper aims to enhance the operational flexibility of AC/DC hybrid distribution networks by proposing a flexibility-oriented optimization framework that addresses the growing uncertainties. Notably, a comprehensive evaluation method for operational flexibility assessment is first established. Based on this, this paper further proposes a flexibility-oriented operation optimization model using the distributionally robust chance-constrained (DRCC) method. A customized solution method utilizing second-order cone relaxation and sample average approximation (SAA) is also introduced. The results of case studies indicate that the flexibility of AC/DC hybrid distribution networks is enhanced through sharing energy storage among multiple feeders, adaptive reactive power regulation using soft open points (SOPs) and static var compensators (SVCs), and power transfer between feeders via SOPs.

Suggested Citation

  • Yue Chen & Qiuyu Lu & Kaiyue Zeng & Yinguo Yang & Pingping Xie, 2024. "Flexibility-Oriented AC/DC Hybrid Grid Optimization Using Distributionally Robust Chance-Constrained Method," Energies, MDPI, vol. 17(19), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4902-:d:1489518
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    References listed on IDEAS

    as
    1. Li, Shuhan & Li, Zhigang & Shahidehpour, Mohammad & Huang, Wenjing & Zheng, J.H., 2024. "Dispatchable region for distributed renewable energy generation in reconfigurable AC–DC distribution networks with soft open points," Applied Energy, Elsevier, vol. 371(C).
    2. Li, Junkai & Ge, Shaoyun & Zhang, Shida & Xu, Zhengyang & Wang, Liyong & Wang, Chengshan & Liu, Hong, 2022. "A multi-objective stochastic-information gap decision model for soft open points planning considering power fluctuation and growth uncertainty," Applied Energy, Elsevier, vol. 317(C).
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