IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i10p2511-d1654718.html
   My bibliography  Save this article

Wind–Photovoltaic–Hydropower Joint Output Model Study Based on Probability Distribution and Correlation Analysis

Author

Listed:
  • Ligui Wu

    (China Yangtze Power Co., Ltd., Yichang 443000, China
    School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China)

  • Benhong Wang

    (China Yangtze Power Co., Ltd., Yichang 443000, China)

  • Peng Zhang

    (China Yangtze Power Co., Ltd., Yichang 443000, China)

  • Yiming Ke

    (School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China)

  • Fangqing Zhang

    (School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China)

  • Jiang Guo

    (School of Power and Mechanical Engineering, Wuhan University, Wuhan 430072, China)

Abstract

To maximize the consumption of renewable energy and improve the reliability of power systems, the development of wind–photovoltaic–hydropower complementary power systems is promising, utilizing the dynamic regulation characteristics of hydropower. Firstly, the complementarity of wind–photovoltaic–hydropower is analyzed, where output characteristics of wind, photovoltaics, and hydropower are introduced, and output models related to wind speed, light intensity, and water level are established. Furthermore, the probability distribution of wind and photovoltaic output is calculated with the maximum likelihood method, and a correlation analysis between wind and photovoltaic output is conducted, where a wind–photovoltaic joint output model is established. Lastly, the k-means clustering algorithm is adopted to process typical scenarios of wind–photovoltaic joint output, and a case study is conducted to validate the wind–photovoltaic–hydropower joint output model. In configuring wind and photovoltaic output reasonably, the amount of abandoned wind and abandoned light is decreased significantly, while the reliability of the power system is improved.

Suggested Citation

  • Ligui Wu & Benhong Wang & Peng Zhang & Yiming Ke & Fangqing Zhang & Jiang Guo, 2025. "Wind–Photovoltaic–Hydropower Joint Output Model Study Based on Probability Distribution and Correlation Analysis," Energies, MDPI, vol. 18(10), pages 1-12, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2511-:d:1654718
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/10/2511/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/10/2511/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tianlei Zang & Shijun Wang & Zian Wang & Chuangzhi Li & Yunfei Liu & Yujian Xiao & Buxiang Zhou, 2024. "Integrated Planning and Operation Dispatching of Source–Grid–Load–Storage in a New Power System: A Coupled Socio–Cyber–Physical Perspective," Energies, MDPI, vol. 17(12), pages 1-43, June.
    2. Papaefthymiou, G. & Dragoon, Ken, 2016. "Towards 100% renewable energy systems: Uncapping power system flexibility," Energy Policy, Elsevier, vol. 92(C), pages 69-82.
    3. Yanan Chen & Ming Zhao & Zhengxian Liu & Jianlong Ma & Lei Yang, 2025. "Comparative Analysis of Offshore Wind Resources and Optimal Wind Speed Distribution Models in China and Europe," Energies, MDPI, vol. 18(5), pages 1-51, February.
    4. Liao, Cuiping & Jochem, Eberhard & Zhang, Yi & Farid, Nida R., 2010. "Wind power development and policies in China," Renewable Energy, Elsevier, vol. 35(9), pages 1879-1886.
    5. Lu, Bin & Blakers, Andrew & Stocks, Matthew, 2017. "90–100% renewable electricity for the South West Interconnected System of Western Australia," Energy, Elsevier, vol. 122(C), pages 663-674.
    Full references (including those not matched with items on IDEAS)

    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. Deng, Xu & Lv, Tao & Meng, Xiangyun & Li, Cong & Hou, Xiaoran & Xu, Jie & Wang, Yinhao & Liu, Feng, 2024. "Assessing the carbon emission reduction effect of flexibility option for integrating variable renewable energy," Energy Economics, Elsevier, vol. 132(C).
    2. Gharibpour, Hassan & Aminifar, Farrokh & Rahmati, Iman & Keshavarz, Arezou, 2021. "Dual variable decomposition to discriminate the cost imposed by inflexible units in electricity markets," Applied Energy, Elsevier, vol. 287(C).
    3. Li, X. & Hubacek, K. & Siu, Y.L., 2012. "Wind power in China – Dream or reality?," Energy, Elsevier, vol. 37(1), pages 51-60.
    4. Yuan, Jiahai & Na, Chunning & Xu, Yan & Zhao, Changhong, 2015. "Wind turbine manufacturing in China: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1235-1244.
    5. Shih-Chieh Huang & Shang-Lien Lo & Yen-Ching Lin, 2013. "To Re-Explore the Causality between Barriers to Renewable Energy Development: A Case Study of Wind Energy," Energies, MDPI, vol. 6(9), pages 1-24, August.
    6. Sun, Shengpeng & Liu, Fengliang & Xue, Song & Zeng, Ming & Zeng, Fanxiao, 2015. "Review on wind power development in China: Current situation and improvement strategies to realize future development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 589-599.
    7. Lago, Jesus & Poplavskaya, Ksenia & Suryanarayana, Gowri & De Schutter, Bart, 2021. "A market framework for grid balancing support through imbalances trading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    8. Obara, Shin'ya & Ito, Yuji & Okada, Masaki, 2018. "Optimization algorithm for power-source arrangement that levels the fluctuations in wide-area networks of renewable energy," Energy, Elsevier, vol. 142(C), pages 447-461.
    9. Lauven, Lars-Peter & Geldermann, Jutta & Desideri, Umberto, 2019. "Estimating the revenue potential of flexible biogas plants in the power sector," Energy Policy, Elsevier, vol. 128(C), pages 402-410.
    10. Copp, David A. & Nguyen, Tu A. & Byrne, Raymond H. & Chalamala, Babu R., 2022. "Optimal sizing of distributed energy resources for planning 100% renewable electric power systems," Energy, Elsevier, vol. 239(PE).
    11. Zhang, Pan, 2019. "Do energy intensity targets matter for wind energy development? Identifying their heterogeneous effects in Chinese provinces with different wind resources," Renewable Energy, Elsevier, vol. 139(C), pages 968-975.
    12. repec:osf:osfxxx:hsbry_v1 is not listed on IDEAS
    13. Ruppert, Leopold & Schürhuber, Robert & List, Bernhard & Lechner, Alois & Bauer, Christian, 2017. "An analysis of different pumped storage schemes from a technological and economic perspective," Energy, Elsevier, vol. 141(C), pages 368-379.
    14. Martínez-Jaramillo, Juan Esteban & van Ackere, Ann & Larsen, Erik, 2023. "Long term impacts of climate change on the transition towards renewables in Switzerland," Energy, Elsevier, vol. 263(PE).
    15. Wang, Zhu & Liu, Ming & Zhao, Yongliang & Wang, Chaoyang & Chong, Daotong & Yan, Junjie, 2020. "Flexibility and efficiency enhancement for double-reheat coal-fired power plants by control optimization considering boiler heat storage," Energy, Elsevier, vol. 201(C).
    16. Chen, Siyuan & Liu, Pei & Li, Zheng, 2020. "Low carbon transition pathway of power sector with high penetration of renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    17. Lema, Rasmus & Berger, Axel & Schmitz, Hubert, 2012. "China’s impact on the global wind power industry," IDOS Discussion Papers 16/2012, German Institute of Development and Sustainability (IDOS).
    18. Aifeng Lv & Taohui Li & Wenxiang Zhang & Yonghao Liu, 2022. "Spatiotemporal Distribution and Complementarity of Wind and Solar Energy in China," Energies, MDPI, vol. 15(19), pages 1-16, October.
    19. Liu, Xuemei, 2013. "The value of holding scarce wind resource—A cause of overinvestment in wind power capacity in China," Energy Policy, Elsevier, vol. 63(C), pages 97-100.
    20. Doda, Baran & Fankhauser, Sam, 2020. "Climate policy and power producers: The distribution of pain and gain," Energy Policy, Elsevier, vol. 138(C).
    21. Bertsch, Valentin & Di Cosmo, Valeria, 2018. "Are Renewables Profitable in 2030? A Comparison between Wind and Solar across Europe," ESP: Energy Scenarios and Policy 276178, Fondazione Eni Enrico Mattei (FEEM).

    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:gam:jeners:v:18:y:2025:i:10:p:2511-:d:1654718. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.