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An effective reserve capacity optimization method for power systems considering operational reliability with weather conditions

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Listed:
  • Dai, Wei
  • Shen, Haoran
  • Liu, Hui
  • Shi, Bochen

Abstract

A reasonable power system reserve is crucial for mitigating uncertain risks. However, determining an effective reserve that achieves both reliability and economics is challenging due to variable operating conditions and complex reliability calculations. This study proposes a reserve capacity optimization method that is embedded in operational reliability, considering multiple uncertainties. A set of operational reliability models for equipment is developed based on the operational status (current) and weather conditions (e.g., freezing rain, temperature, and wind speed). To reduce the computational complexity, a general analytical operational reliability method is proposed based on polynomial chaos expansion, considering the uncertainties of renewable energy, loads, and equipment failures. Using these analytical formulations, a two-stage reserve optimization model considering operational reliability is transformed into a single-stage optimization model, thereby enhancing the computational efficiency without compromising accuracy. Results demonstrate that the proposed method achieved reasonable reserve allocation with fast computation, balancing reliability and economics under variable operating conditions.

Suggested Citation

  • Dai, Wei & Shen, Haoran & Liu, Hui & Shi, Bochen, 2025. "An effective reserve capacity optimization method for power systems considering operational reliability with weather conditions," Applied Energy, Elsevier, vol. 390(C).
    • Handle: RePEc:eee:appene:v:390:y:2025:i:c:s0306261925005434
    DOI: 10.1016/j.apenergy.2025.125813
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    References listed on IDEAS

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    1. Ali Kadhem, Athraa & Abdul Wahab, Noor Izzri & Aris, Ishak & Jasni, Jasronita & Abdalla, Ahmed N., 2017. "Computational techniques for assessing the reliability and sustainability of electrical power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1175-1186.
    2. Wang, Yi & Yang, Zhifang & Yu, Juan & Fang, Xinxin, 2020. "Revisit the electricity price formulation: A formal definition, proofs, and examples," Energy, Elsevier, vol. 200(C).
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