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Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling

Author

Listed:
  • Wenfeng Yao

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Ziyu Huo

    (Department of Electrical Engineering, Tsinghua University, Beijing 610213, China)

  • Jin Zou

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Chen Wu

    (Yunnan Power Grid Co., Ltd., Kunming 100084, China)

  • Jiayang Wang

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Xiang Wang

    (Department of Electrical Engineering, Tsinghua University, Beijing 610213, China)

  • Siyu Lu

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Yigong Xie

    (Yunnan Power Grid Co., Ltd., Kunming 100084, China)

  • Yingjun Zhuo

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Jinbing Liang

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Run Huang

    (Yunnan Power Grid Co., Ltd., Kunming 100084, China)

  • Ming Cheng

    (Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China)

  • Zongxiang Lu

    (Department of Electrical Engineering, Tsinghua University, Beijing 610213, China)

Abstract

In order to consider the impact of source-load uncertainty on traditional power system planning methods, a medium- and long-term optimization planning method based on source-load uncertainty modeling and time-series production simulation is proposed. First, a new energy output probability model is developed using non-parametric kernel density estimation, and the spatial correlation of the new energy output is described using pair-copula theory to model the uncertainty analysis of the new energy output. Secondly, a large number of source-load scenarios are generated using the Markov chain Monte Carlo simulation method, and the optimal selection method for discrete state numbers is provided, and then the scenario reduction is carried out using the fast forward elimination technology. Finally, the typical time-series curves of the source-load uncertainty characteristics obtained are incorporated into the optimization planning method together with various flexible resources, such as the demand-side response and energy storage, and the rationality of the planning scheme is judged and optimized based on key indicators such as the cost, wind–light abandonment rate, and loss-of-load rate. Based on the above methods, this paper offers an example of the power supply planning scheme for a certain region in the next 30 years, providing effective guidance for the development of new energy in the region.

Suggested Citation

  • Wenfeng Yao & Ziyu Huo & Jin Zou & Chen Wu & Jiayang Wang & Xiang Wang & Siyu Lu & Yigong Xie & Yingjun Zhuo & Jinbing Liang & Run Huang & Ming Cheng & Zongxiang Lu, 2024. "Medium- and Long-Term Power System Planning Method Based on Source-Load Uncertainty Modeling," Energies, MDPI, vol. 17(20), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5088-:d:1497843
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    References listed on IDEAS

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    1. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
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