IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v204y2023icp359-371.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122019243
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.12.128?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. 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).
    3. 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).
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    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. 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).
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. 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).
    19. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
    20. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianhua Jiang & Bo Ming & Qiang Huang & Qingjun Bai, 2024. "Operational Robustness Assessment of the Hydro-Based Hybrid Generation System under Deep Uncertainties," Energies, MDPI, vol. 17(8), pages 1-18, April.
    2. 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).
    3. Cheng, Qian & Liu, Pan & Feng, Maoyuan & Cheng, Lei & Ming, Bo & Luo, Xinran & Liu, Weibo & Xu, Weifeng & Huang, Kangdi & Xia, Jun, 2023. "Complementary operation with wind and photovoltaic power induces the decrease in hydropower efficiency," Applied Energy, Elsevier, vol. 339(C).
    4. Sun, Longgang & Xu, Hongyang & Li, Chenxi & Guo, Pengcheng & Xu, Zhuofei, 2024. "Unsteady assessment and alleviation of inter-blade vortex in Francis turbine," Applied Energy, Elsevier, vol. 358(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Cheng, Qian & Liu, Pan & Feng, Maoyuan & Cheng, Lei & Ming, Bo & Luo, Xinran & Liu, Weibo & Xu, Weifeng & Huang, Kangdi & Xia, Jun, 2023. "Complementary operation with wind and photovoltaic power induces the decrease in hydropower efficiency," Applied Energy, Elsevier, vol. 339(C).
    3. Li, He & Liu, Pan & Guo, Shenglian & Zuo, Qiting & Cheng, Lei & Tao, Jie & Huang, Kangdi & Yang, Zhikai & Han, Dongyang & Ming, Bo, 2022. "Integrating teleconnection factors into long-term complementary operating rules for hybrid power systems: A case study of Longyangxia hydro-photovoltaic plant in China," Renewable Energy, Elsevier, vol. 186(C), pages 517-534.
    4. 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).
    5. Cheng, Qian & Liu, Pan & Xia, Qian & Cheng, Lei & Ming, Bo & Zhang, Wei & Xu, Weifeng & Zheng, Yalian & Han, Dongyang & Xia, Jun, 2023. "An analytical method to evaluate curtailment of hydro–photovoltaic hybrid energy systems and its implication under climate change," Energy, Elsevier, vol. 278(C).
    6. Tan, Qiaofeng & Zhang, Ziyi & Wen, Xin & Fang, Guohua & Xu, Shuo & Nie, Zhuang & Wang, Yanling, 2024. "Risk control of hydropower-photovoltaic multi-energy complementary scheduling based on energy storage allocation," Applied Energy, Elsevier, vol. 358(C).
    7. Jiang, Jianhua & Ming, Bo & Huang, Qiang & Guo, Yi & Shang, Jia’nan & Jurasz, Jakub & Liu, Pan, 2023. "A holistic techno-economic evaluation framework for sizing renewable power plant in a hydro-based hybrid generation system," Applied Energy, Elsevier, vol. 348(C).
    8. Wang, Yanling & Wen, Xin & Su, Huaying & Qin, Jisen & Kong, Linghui, 2023. "Real-time dispatch of hydro-photovoltaic (PV) hybrid system based on dynamic load reserve capacity," Energy, Elsevier, vol. 285(C).
    9. Lu, Na & Wang, Guangyan & Su, Chengguo & Ren, Zaimin & Peng, Xiaoyue & Sui, Quan, 2024. "Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties," Applied Energy, Elsevier, vol. 353(PA).
    10. Li, Xudong & Yang, Weijia & Liao, Yiwen & Zhang, Shushu & Zheng, Yang & Zhao, Zhigao & Tang, Maojia & Cheng, Yongguang & Liu, Pan, 2024. "Short-term risk-management for hydro-wind-solar hybrid energy system considering hydropower part-load operating characteristics," Applied Energy, Elsevier, vol. 360(C).
    11. Li, Yan & Ming, Bo & Huang, Qiang & Wang, Yimin & Liu, Pan & Guo, Pengcheng, 2022. "Identifying effective operating rules for large hydro–solar–wind hybrid systems based on an implicit stochastic optimization framework," Energy, Elsevier, vol. 245(C).
    12. 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.
    13. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    14. Ma, Chao & Xu, Ximeng & Pang, Xiulan & Li, Xiaofeng & Zhang, Pengfei & Liu, Lu, 2024. "Scenario-based ultra-short-term rolling optimal operation of a photovoltaic-energy storage system under forecast uncertainty," Applied Energy, Elsevier, vol. 356(C).
    15. Yang, Zhikai & Liu, Pan & Cheng, Lei & Liu, Deli & Ming, Bo & Li, He & Xia, Qian, 2021. "Sizing utility-scale photovoltaic power generation for integration into a hydropower plant considering the effects of climate change: A case study in the Longyangxia of China," Energy, Elsevier, vol. 236(C).
    16. Han, Shuo & Yuan, Yifan & He, Mengjiao & Zhao, Ziwen & Xu, Beibei & Chen, Diyi & Jurasz, Jakub, 2024. "A novel day-ahead scheduling model to unlock hydropower flexibility limited by vibration zones in hydropower-variable renewable energy hybrid system," Applied Energy, Elsevier, vol. 356(C).
    17. Gong, Yu & Liu, Pan & Ming, Bo & Feng, Maoyuan & Huang, Kangdi & Wang, Yibo, 2022. "Identifying the functional form of operating rules for hydro–photovoltaic hybrid power systems," Energy, Elsevier, vol. 243(C).
    18. 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).
    19. 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).
    20. Tan, Qiaofeng & Nie, Zhuang & Wen, Xin & Su, Huaying & Fang, Guohua & Zhang, Ziyi, 2024. "Complementary scheduling rules for hybrid pumped storage hydropower-photovoltaic power system reconstructing from conventional cascade hydropower stations," Applied Energy, Elsevier, vol. 355(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:204:y:2023:i:c:p:359-371. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.