IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i7p1648-d1620682.html
   My bibliography  Save this article

Complementary Characteristics Between Hydro-Solar-Wind Power Factors in the Upper Yellow River Region During 1979~2018

Author

Listed:
  • Jiongwei Cao

    (State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China)

  • Xiang Li

    (State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China
    State Key Laboratory of Basin Water Cycle Simulation and Regulation, China Institute of Resources and Hydropower Research, Beijing 100038, China)

  • Huimin Zuo

    (School of Hydraulic Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China)

  • Jingyang Wang

    (State Key Laboratory of Basin Water Cycle Simulation and Regulation, China Institute of Resources and Hydropower Research, Beijing 100038, China)

  • Lizhen Wang

    (State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China
    State Key Laboratory of Basin Water Cycle Simulation and Regulation, China Institute of Resources and Hydropower Research, Beijing 100038, China)

Abstract

In this paper, we focus on the four provinces (Qinghai, Gansu, Ningxia, and Inner Mongolia) in the upper Yellow River region and conduct a quantitative analysis of the spatiotemporal distributions of the precipitation (P), shortwave radiation (R), and wind speed (W) from 1979 to 2018 using the China Meteorological Forcing Dataset. The complementarity of these power factors is analyzed across multiple time scales and resolutions. A complementarity coefficient is introduced by integrating three correlation coefficients to evaluate the interrelationship between pairs of power factors. Additionally, the probability density distributions of individual and pairs of power factors are examined at the Longyangxia Clean Energy Base in Qinghai Province. The complementarity coefficients between the P and R, P and W, and R and W exhibited significant variations across regions. The complementarity coefficients for P and R were negative, ranging from −0.019 to −0.029 at the 3 h resolution and from −0.384 to −0.429 at the daily resolution, indicating a strong complementarity at the longer temporal resolution. The complementarity coefficients for P and W were positive, ranging from 0.029 to 0.047 at the 3 h resolution and from 0.038 to 0.065 at the daily resolution, indicating a stable correlation at different resolutions. The complementarity coefficients for R and W changed from positive at the 3 h resolution to negative at the daily resolution, indicating that the correlation changes to complementarity at different resolutions. The annual joint probability density is highest for daily precipitation ranging from 276.0 to 304.4 mm, daily shortwave radiation between 1832.6 and 1847.5 kW/m 2 , and daily mean wind speed varying from 1.7 to 1.8 m/s.

Suggested Citation

  • Jiongwei Cao & Xiang Li & Huimin Zuo & Jingyang Wang & Lizhen Wang, 2025. "Complementary Characteristics Between Hydro-Solar-Wind Power Factors in the Upper Yellow River Region During 1979~2018," Energies, MDPI, vol. 18(7), pages 1-25, March.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1648-:d:1620682
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/7/1648/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/7/1648/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Spatial and temporal assessments of complementarity for renewable energy resources in China," Energy, Elsevier, vol. 177(C), pages 262-275.
    2. Wang, Qiang & Kwan, Mei-Po & Fan, Jie & Zhou, Kan & Wang, Ya-Fei, 2019. "A study on the spatial distribution of the renewable energy industries in China and their driving factors," Renewable Energy, Elsevier, vol. 139(C), pages 161-175.
    3. Han, Shuang & Zhang, Lu-na & Liu, Yong-qian & Zhang, Hao & Yan, Jie & Li, Li & Lei, Xiao-hui & Wang, Xu, 2019. "Quantitative evaluation method for the complementarity of wind–solar–hydro power and optimization of wind–solar ratio," Applied Energy, Elsevier, vol. 236(C), pages 973-984.
    4. Wei Fang & Cheng Yang & Dengfeng Liu & Qiang Huang & Bo Ming & Long Cheng & Lu Wang & Gang Feng & Jianan Shang, 2023. "Assessment of Wind and Solar Power Potential and Their Temporal Complementarity in China’s Northwestern Provinces: Insights from ERA5 Reanalysis," Energies, MDPI, vol. 16(20), pages 1-23, October.
    5. D’Isidoro, Massimo & Briganti, Gino & Vitali, Lina & Righini, Gaia & Adani, Mario & Guarnieri, Guido & Moretti, Lorenzo & Raliselo, Muso & Mahahabisa, Mabafokeng & Ciancarella, Luisella & Zanini, Gabr, 2020. "Estimation of solar and wind energy resources over Lesotho and their complementarity by means of WRF yearly simulation at high resolution," Renewable Energy, Elsevier, vol. 158(C), pages 114-129.
    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. Pedruzzi, Rizzieri & Silva, Allan Rodrigues & Soares dos Santos, Thalyta & Araujo, Allan Cavalcante & Cotta Weyll, Arthur Lúcide & Lago Kitagawa, Yasmin Kaore & Nunes da Silva Ramos, Diogo & Milani de, 2023. "Review of mapping analysis and complementarity between solar and wind energy sources," Energy, Elsevier, vol. 283(C).
    2. Diana Cantor & Andrés Ochoa & Oscar Mesa, 2022. "Total Variation-Based Metrics for Assessing Complementarity in Energy Resources Time Series," Sustainability, MDPI, vol. 14(14), pages 1-15, July.
    3. Harrison-Atlas, Dylan & Murphy, Caitlin & Schleifer, Anna & Grue, Nicholas, 2022. "Temporal complementarity and value of wind-PV hybrid systems across the United States," Renewable Energy, Elsevier, vol. 201(P1), pages 111-123.
    4. Gao, Yang & Meng, Yangyang & Dong, Guanpeng & Ma, Shaoxiu & Miao, Changhong & Xiao, Jianhua & Mao, Shuting & Shao, Lili, 2024. "The wind-solar hybrid energy could serve as a stable power source at multiple time scale in China mainland," Energy, Elsevier, vol. 305(C).
    5. Henao, Felipe & Viteri, Juan P. & Rodríguez, Yeny & Gómez, Juan & Dyner, Isaac, 2020. "Annual and interannual complementarities of renewable energy sources in Colombia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    6. 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).
    7. Ana Rita Silva & Ana Estanqueiro, 2022. "From Wind to Hybrid: A Contribution to the Optimal Design of Utility-Scale Hybrid Power Plants," Energies, MDPI, vol. 15(7), pages 1-19, April.
    8. Wei Fang & Cheng Yang & Dengfeng Liu & Qiang Huang & Bo Ming & Long Cheng & Lu Wang & Gang Feng & Jianan Shang, 2023. "Assessment of Wind and Solar Power Potential and Their Temporal Complementarity in China’s Northwestern Provinces: Insights from ERA5 Reanalysis," Energies, MDPI, vol. 16(20), pages 1-23, October.
    9. Taohui Li & Yonghao Liu & Aifeng Lv, 2024. "Review of Research on the Present Situation of Development and Resource Potential of Wind and Solar Energy in China," Energies, MDPI, vol. 17(16), pages 1-14, August.
    10. Chen, Zhuo & Li, Wei & Wang, Xiaoxuan & Bai, Jingjie & Wang, Xiuquan & Guo, Junhong, 2024. "Evaluating wind and solar complementarity in China: Considering climate change and source-load matching dynamics," Energy, Elsevier, vol. 312(C).
    11. Wang, Fengjuan & Xu, Jiuping & Wang, Qingchun, 2024. "Complementary operation based sizing and scheduling strategy for hybrid hydro-PV-wind generation systems connected to long-distance transmission lines," Applied Energy, Elsevier, vol. 364(C).
    12. Xiaomei Ma & Yongqian Liu & Jie Yan & Han Wang, 2023. "A WGAN-GP-Based Scenarios Generation Method for Wind and Solar Power Complementary Study," Energies, MDPI, vol. 16(7), pages 1-20, March.
    13. Jani, Hardik K. & Kachhwaha, Surendra Singh & Nagababu, Garlapati & Das, Alok, 2022. "Temporal and spatial simultaneity assessment of wind-solar energy resources in India by statistical analysis and machine learning clustering approach," Energy, Elsevier, vol. 248(C).
    14. Yanqian Li & Yanlai Zhou & Yuxuan Luo & Zhihao Ning & Chong-Yu Xu, 2024. "Boosting the Development and Management of Wind Energy: Self-Organizing Map Neural Networks for Clustering Wind Power Outputs," Energies, MDPI, vol. 17(21), pages 1-15, November.
    15. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    16. Zhang, Yusheng & Ma, Chao & Yang, Yang & Pang, Xiulan & Lian, Jijian & Wang, Xin, 2022. "Capacity configuration and economic evaluation of a power system integrating hydropower, solar, and wind," Energy, Elsevier, vol. 259(C).
    17. He, Yi & Guo, Su & Zhou, Jianxu & Wu, Feng & Huang, Jing & Pei, Huanjin, 2021. "The many-objective optimal design of renewable energy cogeneration system," Energy, Elsevier, vol. 234(C).
    18. Wang, Han & Yan, Jie & Han, Shuang & Liu, Yongqian, 2020. "Switching strategy of the low wind speed wind turbine based on real-time wind process prediction for the integration of wind power and EVs," Renewable Energy, Elsevier, vol. 157(C), pages 256-272.
    19. Yinhui Wang & Yugang He & Xiaodan Gao, 2025. "Synergizing Renewable Energy and Circular Economy Strategies: Pioneering Pathways to Environmental Sustainability," Sustainability, MDPI, vol. 17(5), pages 1-22, February.
    20. Zhang, Jing & Lei, Xiaohui & Chen, Bin & Song, Yongyu, 2019. "Analysis of blue water footprint of hydropower considering allocation coefficients for multi-purpose reservoirs," Energy, Elsevier, vol. 188(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:7:p:1648-:d:1620682. 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.