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Integrated Transmission Network Planning by Considering Wind Power’s Uncertainty and Disasters

Author

Listed:
  • Yishan Shi

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Ruipeng Guo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yuchen Tang

    (State Grid Fujian Economic Research Institute, Fuzhou 350011, China)

  • Yi Lin

    (State Grid Fujian Economic Research Institute, Fuzhou 350011, China)

  • Zhanxin Yang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

The penetration of wind turbines and other power sources with strong uncertainty into the grid has increased in recent years. It has brought significant technical challenges to power systems’ operation. The volatility and intermittency of wind power increase the risk of insufficient transmission capacity of the lines. Therefore, the traditional deterministic planning methods for transmission grids are no longer fully applicable. On the other hand, the frequent disasters in recent years have posed a great threat to the power system, especially for the transmission grid. This requires the design of transmission lines with high design standards, such as skeleton networks, to withstand disasters. With the aim to address these problems, a bi-level integrated network planning model for the transmission grid is developed by considering wind power’s uncertainty and load guarantee under disasters. Chance constraints are used in the model to characterize wind power’s uncertainty, and a skeleton network is adopted to cope with disasters. Moreover, based on a convex relaxation method, the chance constraints are converted into the probabilistic inequalities to be solved. The proposed method is simulated in the IEEE 118 bus system, and the obtained network planning scheme is further analyzed in the scenario tests. And the result of the tests proves the validity and reasonableness of the proposed method.

Suggested Citation

  • Yishan Shi & Ruipeng Guo & Yuchen Tang & Yi Lin & Zhanxin Yang, 2023. "Integrated Transmission Network Planning by Considering Wind Power’s Uncertainty and Disasters," Energies, MDPI, vol. 16(14), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5336-:d:1192583
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    References listed on IDEAS

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    1. Dong, Wei & Chen, Xianqing & Yang, Qiang, 2022. "Data-driven scenario generation of renewable energy production based on controllable generative adversarial networks with interpretability," Applied Energy, Elsevier, vol. 308(C).
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    Cited by:

    1. Zhou Su & Guoqing Yang & Lixiao Yao & Qingqing Zhou & Yuhan Zhang, 2024. "Optimization of Provincial Power Source Structure Planning in Northwestern China Based on Time-Series Production Simulation," Energies, MDPI, vol. 17(19), pages 1-14, September.
    2. Yun Yang & Zichao Meng & Guobing Wu & Zhanxin Yang & Ruipeng Guo, 2025. "A Probabilistic Reserve Decision-Making Method Based on Cumulative Probability Approximation for High-Penetration Renewable Energy Power System," Energies, MDPI, vol. 18(10), pages 1-13, May.

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