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Random Fuzzy Optimization Model for Short-Term Hydropower Scheduling Considering Uncertainty of Power Load

Author

Listed:
  • Liu Yuan

    (Huazhong University of Science and Technology)

  • Jianzhong Zhou

    (Huazhong University of Science and Technology)

  • Zijun Mai

    (Huazhong University of Science and Technology)

  • Yuanzheng Li

    (Huazhong University of Science and Technology)

Abstract

This paper proposes a random fuzzy optimization (RFO) model for short-term hydropower scheduling, in order to avoid frequent unit switches owing to uncertainty of the power load. The cascade hydropower stations of Qing River in China are firstly introduced for research, and the power load error of the cascade is described. Defined as a random fuzzy variable, the error is analyzed and its distribution is derived to signify the uncertainty. Then random fuzzy programming is integrated into short-term hydropower scheduling to develop the RFO model, with more attention payed to unit spare capacity, while satisfying the demand of power grids. Meanwhile, an applicable solution searching strategy is proposed to solve the model. Simulation results of random fuzzy optimization of the cascade prove that the strategy is practical and the developed model is effective to avoid frequent unit switches. The method also can provide available references for other cascade dispatching center and hydropower stations with the same plight.

Suggested Citation

  • Liu Yuan & Jianzhong Zhou & Zijun Mai & Yuanzheng Li, 2017. "Random Fuzzy Optimization Model for Short-Term Hydropower Scheduling Considering Uncertainty of Power Load," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2713-2728, July.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:9:d:10.1007_s11269-017-1657-y
    DOI: 10.1007/s11269-017-1657-y
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    References listed on IDEAS

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    1. Liu Yuan & Jianzhong Zhou, 2017. "Self-Optimization System Dynamics Simulation of Real-Time Short Term Cascade Hydropower System Considering Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(7), pages 2127-2140, May.
    2. Schulze, Tim & McKinnon, Ken, 2016. "The value of stochastic programming in day-ahead and intra-day generation unit commitment," Energy, Elsevier, vol. 101(C), pages 592-605.
    3. Shen, Jianjian & Cheng, Chuntian & Cheng, Xiong & Lund, Jay R., 2016. "Coordinated operations of large-scale UHVDC hydropower and conventional hydro energies about regional power grid," Energy, Elsevier, vol. 95(C), pages 433-446.
    4. Chang, XiaoLin & Liu, Xinghong & Zhou, Wei, 2010. "Hydropower in China at present and its further development," Energy, Elsevier, vol. 35(11), pages 4400-4406.
    5. Liu Yuan & Jianzhong Zhou & Chunlong Li & Mengfei Xie & Li Mo, 2016. "Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3347-3361, August.
    6. J. Sreekanth & Bithin Datta & Pranab Mohapatra, 2012. "Optimal Short-term Reservoir Operation with Integrated Long-term Goals," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(10), pages 2833-2850, August.
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    Cited by:

    1. Yang, Zhe & Wang, Yufeng & Yang, Kan, 2022. "The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts," Energy, Elsevier, vol. 241(C).

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