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Refining long-term operation of large hydro–photovoltaic–wind hybrid systems by nesting response functions

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  • Jiang, Jianhua
  • Ming, Bo
  • Liu, Pan
  • Huang, Qiang
  • Guo, Yi
  • Chang, Jianxia
  • Zhang, Wei

Abstract

The traditional long-term operation models of hydro–photovoltaic (PV)–wind hybrid systems (HPWHSs) were formulated on the basis of monthly or ten-day time-scale, and they failed to describe intraday stochastic and fluctuating features of the PV and wind power, resulting in sub-optimal operating rules. To address this issue, we proposed an effective method to refine long-term operating rules for the large HPWHS by nesting a set of response functions. These response functions were derived based on numerous daily operation results, characterizing relationships between long-term hydropower output and residual load, operational risk, and electricity curtailment metrics, respectively. A large HPWHS located in the upper Yellow River basin, Qinghai province, China was selected as a case study. Results showed that the refined operating rules could decrease curtailment rate of the new energy from 17.5% to 9% compared with a standard operation policy. Meanwhile, energy production of the HPWHS and its generation guaranteed rate were increased by 7.7% and 72.7%, respectively, and the residual load fluctuation and operational risk rate were reduced by 35.6% and 23.3%, respectively. Therefore, the proposed long-term operation method is effective for guiding the complementary management of the large HPWHS.

Suggested Citation

  • Jiang, Jianhua & Ming, Bo & Liu, Pan & Huang, Qiang & Guo, Yi & Chang, Jianxia & Zhang, Wei, 2023. "Refining long-term operation of large hydro–photovoltaic–wind hybrid systems by nesting response functions," Renewable Energy, Elsevier, vol. 204(C), pages 359-371.
    • Handle: RePEc:eee:renene:v:204:y:2023:i:c:p:359-371
    DOI: 10.1016/j.renene.2022.12.128
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    References listed on IDEAS

    as
    1. Guo, Yi & Ming, Bo & Huang, Qiang & Liu, Pan & Wang, Yimin & Fang, Wei & Zhang, Wei, 2022. "Evaluating effects of battery storage on day-ahead generation scheduling of large hydro–wind–photovoltaic complementary systems," Applied Energy, Elsevier, vol. 324(C).
    2. Zhang, Yi & Cheng, Chuntian & Cai, Huaxiang & Jin, Xiaoyu & Jia, Zebin & Wu, Xinyu & Su, Huaying & Yang, Tiantian, 2022. "Long-term stochastic model predictive control and efficiency assessment for hydro-wind-solar renewable energy supply system," Applied Energy, Elsevier, vol. 316(C).
    3. Wang, Zhenni & Wen, Xin & Tan, Qiaofeng & Fang, Guohua & Lei, Xiaohui & Wang, Hao & Yan, Jinyue, 2021. "Potential assessment of large-scale hydro-photovoltaic-wind hybrid systems on a global scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    4. Cheng, Qian & Liu, Pan & Xia, Jun & Ming, Bo & Cheng, Lei & Chen, Jie & Xie, Kang & Liu, Zheyuan & Li, Xiao, 2022. "Contribution of complementary operation in adapting to climate change impacts on a large-scale wind–solar–hydro system: A case study in the Yalong River Basin, China," Applied Energy, Elsevier, vol. 325(C).
    5. Wen, Xin & Sun, Yuanliang & Tan, Qiaofeng & Tang, Zhengyang & Wang, Zhenni & Liu, Zhehua & Ding, Ziyu, 2022. "Optimizing the sizes of wind and photovoltaic plants complementarily operating with cascade hydropower stations: Balancing risk and benefit," Applied Energy, Elsevier, vol. 306(PA).
    6. Li, He & Liu, Pan & Guo, Shenglian & Ming, Bo & Cheng, Lei & Yang, Zhikai, 2019. "Long-term complementary operation of a large-scale hydro-photovoltaic hybrid power plant using explicit stochastic optimization," Applied Energy, Elsevier, vol. 238(C), pages 863-875.
    7. Gong, Yu & Liu, Pan & Ming, Bo & Li, Dingfang, 2021. "Identifying the effect of forecast uncertainties on hybrid power system operation: A case study of Longyangxia hydro–photovoltaic plant in China," Renewable Energy, Elsevier, vol. 178(C), pages 1303-1321.
    8. Mazidi, Mohammadreza & Monsef, Hassan & Siano, Pierluigi, 2016. "Design of a risk-averse decision making tool for smart distribution network operators under severe uncertainties: An IGDT-inspired augment ε-constraint based multi-objective approach," Energy, Elsevier, vol. 116(P1), pages 214-235.
    9. Li, He & Liu, Pan & Guo, Shenglian & Cheng, Lei & Huang, Kangdi & Feng, Maoyuan & He, Shaokun & Ming, Bo, 2021. "Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter," Applied Energy, Elsevier, vol. 301(C).
    10. Tan, Qiaofeng & Wen, Xin & Sun, Yuanliang & Lei, Xiaohui & Wang, Zhenni & Qin, Guanghua, 2021. "Evaluation of the risk and benefit of the complementary operation of the large wind-photovoltaic-hydropower system considering forecast uncertainty," Applied Energy, Elsevier, vol. 285(C).
    11. Huang, Kangdi & Liu, Pan & Ming, Bo & Kim, Jong-Suk & Gong, Yu, 2021. "Economic operation of a wind-solar-hydro complementary system considering risks of output shortage, power curtailment and spilled water," Applied Energy, Elsevier, vol. 290(C).
    12. Xiao, Hao & Pei, Wei & Deng, Wei & Ma, Tengfei & Zhang, Shizhong & Kong, Li, 2021. "Enhancing risk control ability of distribution network for improved renewable energy integration through flexible DC interconnection," Applied Energy, Elsevier, vol. 284(C).
    13. Ming, Bo & Liu, Pan & Guo, Shenglian & Zhang, Xiaoqi & Feng, Maoyuan & Wang, Xianxun, 2017. "Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions," Applied Energy, Elsevier, vol. 204(C), pages 432-445.
    14. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).
    15. Gong, Yu & Liu, Pan & Ming, Bo & Xu, Weifeng & Huang, Kangdi & Li, Xiao, 2021. "Deriving pack rules for hydro–photovoltaic hybrid power systems considering diminishing marginal benefit of energy," Applied Energy, Elsevier, vol. 304(C).
    16. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhang, Jingwen, 2019. "Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation," Energy, Elsevier, vol. 179(C), pages 268-279.
    17. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
    18. Pinto, Mauro S.S. & Miranda, Vladimiro & Saavedra, Osvaldo R., 2016. "Risk and unit commitment decisions in scenarios of wind power uncertainty," Renewable Energy, Elsevier, vol. 97(C), pages 550-558.
    19. Guo, Yi & Ming, Bo & Huang, Qiang & Wang, Yimin & Zheng, Xudong & Zhang, Wei, 2022. "Risk-averse day-ahead generation scheduling of hydro–wind–photovoltaic complementary systems considering the steady requirement of power delivery," Applied Energy, Elsevier, vol. 309(C).
    20. Xu, Bin & Zhu, Feilin & Zhong, Ping-an & Chen, Juan & Liu, Weifeng & Ma, Yufei & Guo, Le & Deng, Xiaoliang, 2019. "Identifying long-term effects of using hydropower to complement wind power uncertainty through stochastic programming," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    4. He, Yaoyao & Hong, Xiaoyu & Wang, Chao & Qin, Hui, 2023. "Optimal capacity configuration of the hydro-wind-photovoltaic complementary system considering cascade reservoir connection," Applied Energy, Elsevier, vol. 352(C).

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