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A forecast-driven decision-making model for long-term operation of a hydro-wind-photovoltaic hybrid system

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Listed:
  • Ding, Ziyu
  • Wen, Xin
  • Tan, Qiaofeng
  • Yang, Tiantian
  • Fang, Guohua
  • Lei, Xiaohui
  • Zhang, Yu
  • Wang, Hao

Abstract

Hydro-wind-photovoltaic (PV) hybrid system has the potential to increase the integration of renewable energy sources into an existing grid. For the long-term operation of the system, due to the non-storable nature of wind and PV power, it is essentially to decide the optimal long-term carryover storage of cascade reservoirs. However, it remains a challenge due to high uncertainties of long-term forecasts and complicated hydraulic/electrical relationships between cascade reservoirs. In this study, a forecast-driven decision-making model is proposed for the hybrid system, which converts the multi-stage long-term operation process into a two-stage operation problem (including current stage and carryover stage) to avoid using longer-horizon forecast information with lower accuracy. First, the carryover stage energy surfaces (CESs) considering the forecast uncertainties of wind, solar and hydro resources are proposed to characterize carryover stage benefit quantitatively. Then a CESs-based forward decision-making optimization model is developed to guide the long-term operation of a hydro-wind-photovoltaic hybrid system. The applications in a hydro-wind-PV hybrid system of Yalong River basin results show that: compared with conventional operation, 1) power generation increases 9.03%; 2) in terms of the carryover storages control, the reservoir impounding and drawdown timing are delayed, and the drawdown depth is increased, which can be used to formulate better reservoir operation rules.

Suggested Citation

  • Ding, Ziyu & Wen, Xin & Tan, Qiaofeng & Yang, Tiantian & Fang, Guohua & Lei, Xiaohui & Zhang, Yu & Wang, Hao, 2021. "A forecast-driven decision-making model for long-term operation of a hydro-wind-photovoltaic hybrid system," Applied Energy, Elsevier, vol. 291(C).
    • Handle: RePEc:eee:appene:v:291:y:2021:i:c:s0306261921003202
    DOI: 10.1016/j.apenergy.2021.116820
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    Cited by:

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    6. Chaoyang Chen & Hualing Liu & Yong Xiao & Fagen Zhu & Li Ding & Fuwen Yang, 2022. "Power Generation Scheduling for a Hydro-Wind-Solar Hybrid System: A Systematic Survey and Prospect," Energies, MDPI, vol. 15(22), pages 1-31, November.
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