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Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method

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  • Yunhai Zhou

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China
    Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443000, China)

  • Shengkai Guo

    (College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, China
    Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station, China Three Gorges University, Yichang 443000, China)

  • Fei Xu

    (Department of Electrical Engineering, Tsinghua University, Beijing 100000, China)

  • Dai Cui

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, China
    School of Electrical Engineering, Shenyang University of Technology, Shenyang 100084, China)

  • Weichun Ge

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, China
    School of Electrical Engineering, Shenyang University of Technology, Shenyang 100084, China)

  • Xiaodong Chen

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, China)

  • Bo Gu

    (Jinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, China)

Abstract

The wind–heat conflict and wind power uncertainty are the main factors leading to the phenomenon of wind curtailment during the heating period in the northern region of China. In this paper, a multi-time scale optimal scheduling strategy for combined heat and power system is proposed. Considering the temporal dependence of wind power fluctuation, the intra-day wind power scenario generation method is put forward, and both day-ahead and intra-day optimization scheduling models based on the scenario method are established to maximize the system’s revenue. The case analyzes the impacts of the initial heat storage capacity of a heat storage device and different scheduling strategies on system revenue. It is verified that the scheduling strategy can better adapt to wind power uncertainty and improve the absorption capacity of wind power, while ensuring the safety and economical efficiency of system operation.

Suggested Citation

  • Yunhai Zhou & Shengkai Guo & Fei Xu & Dai Cui & Weichun Ge & Xiaodong Chen & Bo Gu, 2020. "Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method," Energies, MDPI, vol. 13(7), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1599-:d:339840
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    References listed on IDEAS

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    1. Bach Hoang Dinh & Thang Trung Nguyen & Nguyen Vu Quynh & Le Van Dai, 2018. "A Novel Method for Economic Dispatch of Combined Heat and Power Generation," Energies, MDPI, vol. 11(11), pages 1-27, November.
    2. Nuytten, Thomas & Claessens, Bert & Paredis, Kristof & Van Bael, Johan & Six, Daan, 2013. "Flexibility of a combined heat and power system with thermal energy storage for district heating," Applied Energy, Elsevier, vol. 104(C), pages 583-591.
    3. Liang Tian & Yunlei Xie & Bo Hu & Xinping Liu & Tuoyu Deng & Huanhuan Luo & Fengqiang Li, 2019. "A Deep Peak Regulation Auxiliary Service Bidding Strategy for CHP Units Based on a Risk-Averse Model and District Heating Network Energy Storage," Energies, MDPI, vol. 12(17), pages 1-27, August.
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    Cited by:

    1. Yuxing Liu & Linjun Zeng & Jie Zeng & Zhenyi Yang & Na Li & Yuxin Li, 2023. "Scheduling Optimization of IEHS with Uncertainty of Wind Power and Operation Mode of CCP," Energies, MDPI, vol. 16(5), pages 1-17, February.

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