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Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization

Author

Listed:
  • Jing Shi

    (State Grid Jiangsu Electric Power Co., Ltd., Economic and Technological Research Institute, Nanjing 210008, China)

  • Jianru Qin

    (Tsinghua Sichuan Energy Internet Research Institute, Chengdu 610213, China)

  • Haibo Li

    (Tsinghua Sichuan Energy Internet Research Institute, Chengdu 610213, China)

  • Zesen Li

    (State Grid Jiangsu Electric Power Co., Ltd., Economic and Technological Research Institute, Nanjing 210008, China)

  • Yi Ge

    (State Grid Jiangsu Electric Power Co., Ltd., Economic and Technological Research Institute, Nanjing 210008, China)

  • Boliang Liu

    (State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210024, China)

Abstract

The volatility and uncertainty associated with the high proportion of wind and PV output in the new power system significantly impact the power and energy balance, making it challenging to accurately assess the risks related to renewable energy abandonment and supply guarantee. Therefore, a probabilistic power and energy balance risk analysis method based on distributed robust optimization is proposed. Firstly, the affine factor and the flexible ramp reserve capacity of thermal power are combined to establish a probabilistic index, which serves to characterize the risk associated with the power and energy balance. Drawing upon the principles of the conditional value at risk theory, the risk indexes of the load shedding power and curtailment power under a certain confidence probability are proposed. Secondly, the probability distribution fuzzy sets of uncertain variables are constructed using the distributionally robust method to measure the Wasserstein distance between different probability distributions. Finally, aiming at minimizing the operation cost of thermal power, the risk cost of power abandonment, and the risk cost of load shedding, a distributed robust optimal scheduling model based on a flexible ramp reserve of thermal power is established.

Suggested Citation

  • Jing Shi & Jianru Qin & Haibo Li & Zesen Li & Yi Ge & Boliang Liu, 2024. "Probabilistic Power and Energy Balance Risk Scheduling Method Based on Distributed Robust Optimization," Energies, MDPI, vol. 17(19), pages 1-21, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4894-:d:1489005
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    References listed on IDEAS

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    1. Lu, Bin & Blakers, Andrew & Stocks, Matthew & Do, Thang Nam, 2021. "Low-cost, low-emission 100% renewable electricity in Southeast Asia supported by pumped hydro storage," Energy, Elsevier, vol. 236(C).
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