IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v396y2025ics0306261925010505.html

From input to output: Unraveling the Spatio - temporal pattern and driving factors of the coupling coordination between wind power efficiency and installed capacity in China

Author

Listed:
  • Liu, Pihui
  • Li, Mengdi
  • Han, Chuanfeng
  • Meng, Lingpeng
  • Shao, Zhiguo

Abstract

As a clean and renewable energy utilization mode, wind power's status in the global energy system is increasingly prominent. Understanding the relationship between its production inputs and generation efficiency is crucial for optimizing the industrial layout. However, existing research often struggles to address the spatio-temporal mismatch and influencing factors of these two aspects. This research uses the SBM - DDF model to assess the wind power generation efficiency across 31 Chinese provinces from 2015 to 2023. The standard deviation ellipse model analyzes the spatio - temporal evolution of wind power generation efficiency and installed capacity, while an improved coupling coordination degree (CCD) model evaluates their interrelationship. Additionally, a spatio-temporal geographically weighted regression model investigates the factors influencing the CCD. The results show that between 2015 and 2023, China's provincial wind power generation efficiency steadily steadily, though regional differences widened. Western and eastern provinces exhibited higher efficiency than central provinces, while wind power installed capacity was concentrated in the southeast-northeast direction, with significant growth in the east. Overall, the CCD between wind power generation efficiency and installed capacity strengthened, particularly in northwest, north China, and eastern regions, with the central region's coordination improving significantly in 2022, forming a “center-periphery” radiation pattern. Initially, factors such as the added value of secondary and tertiary industries, scientific and technological expenditures, and government intervention negatively impacted the CCD, while financial variables and social electricity consumption had a positive effect. By 2023, the impact of government intervention turned positive, while the influence of financial institutions became negative. Regionally, the western region was more significantly affected by these factors than the eastern region.

Suggested Citation

  • Liu, Pihui & Li, Mengdi & Han, Chuanfeng & Meng, Lingpeng & Shao, Zhiguo, 2025. "From input to output: Unraveling the Spatio - temporal pattern and driving factors of the coupling coordination between wind power efficiency and installed capacity in China," Applied Energy, Elsevier, vol. 396(C).
  • Handle: RePEc:eee:appene:v:396:y:2025:i:c:s0306261925010505
    DOI: 10.1016/j.apenergy.2025.126320
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925010505
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2025.126320?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Gao, Chengkang & Zhu, Sulong & An, Nan & Na, Hongming & You, Huan & Gao, Chengbo, 2021. "Comprehensive comparison of multiple renewable power generation methods: A combination analysis of life cycle assessment and ecological footprint," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    2. Zhao, Zhen-yu & Yan, Hong & Zuo, Jian & Tian, Yu-xi & Zillante, George, 2013. "A critical review of factors affecting the wind power generation industry in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 499-508.
    3. He, Yongxiu & Xu, Yang & Pang, Yuexia & Tian, Huiying & Wu, Rui, 2016. "A regulatory policy to promote renewable energy consumption in China: Review and future evolutionary path," Renewable Energy, Elsevier, vol. 89(C), pages 695-705.
    4. Teng, Minmin & Lv, Kunfeng & Han, Chuanfeng & Liu, Pihui, 2025. "A tripartite stochastic evolutionary game for trading strategies under renewable portfolio standards in China’s electric power industry," Renewable Energy, Elsevier, vol. 240(C).
    5. Wang, Richard & Hsu, Shu-Chien & Zheng, Saina & Chen, Jieh-Haur & Li, Xuran Ivan, 2020. "Renewable energy microgrids: Economic evaluation and decision making for government policies to contribute to affordable and clean energy," Applied Energy, Elsevier, vol. 274(C).
    6. Liu, Pihui & Han, Chuanfeng & Liu, Xinghua & Teng, Minmin, 2023. "Assessing the effect of nonfarm income on the household cooking energy transition in rural China," Energy, Elsevier, vol. 267(C).
    7. Li, Mengdi & Han, Chuanfeng & Meng, Lingpeng & Liu, Pihui, 2025. "Spatiotemporal dynamics and factors of renewable energy mismatch in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    8. Papież, Monika & Śmiech, Sławomir & Frodyma, Katarzyna, 2019. "Factors affecting the efficiency of wind power in the European Union countries," Energy Policy, Elsevier, vol. 132(C), pages 965-977.
    9. Wenwei Lian & Bingyan Wang & Tianming Gao & Xiaoyan Sun & Yan Zhang & Hongmei Duan, 2022. "Coordinated Development of Renewable Energy: Empirical Evidence from China," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    10. Tone, Kaoru & Toloo, Mehdi & Izadikhah, Mohammad, 2020. "A modified slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 287(2), pages 560-571.
    11. Zhang, Shijie & Wei, Jing & Chen, Xi & Zhao, Yuhao, 2020. "China in global wind power development: Role, status and impact," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    12. Yunna, Wu & Ruhang, Xu, 2013. "Current status, future potentials and challenges of renewable energy development in Gansu province (Northwest China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 73-86.
    13. Sahu, Bikash Kumar, 2018. "Wind energy developments and policies in China: A short review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1393-1405.
    14. Liu, Chenyu & Zhang, Xuemin & Mei, Shengwei & Zhen, Zhao & Jia, Mengshuo & Li, Zheng & Tang, Haiyan, 2022. "Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness," Applied Energy, Elsevier, vol. 313(C).
    15. Xu, Jiuping & Liu, Tingting, 2020. "Technological paradigm-based approaches towards challenges and policy shifts for sustainable wind energy development," Energy Policy, Elsevier, vol. 142(C).
    16. Ibrahim Yilmaz, 2023. "A Hybrid DEA–Fuzzy COPRAS Approach to the Evaluation of Renewable Energy: A Case of Wind Farms in Turkey," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    17. Teng, Minmin & Lv, Kunfeng & Han, Chuanfeng & Liu, Pihui, 2023. "Trading behavior strategy of power plants and the grid under renewable portfolio standards in China: A tripartite evolutionary game analysis," Energy, Elsevier, vol. 284(C).
    18. Ji, Qiang & Zhang, Dayong, 2019. "How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?," Energy Policy, Elsevier, vol. 128(C), pages 114-124.
    19. Kennedy, Scott & Sgouridis, Sgouris, 2011. "Rigorous classification and carbon accounting principles for low and Zero Carbon Cities," Energy Policy, Elsevier, vol. 39(9), pages 5259-5268, September.
    20. Hu, Rui & Skea, Jim & Hannon, Matthew J., 2018. "Measuring the energy innovation process: An indicator framework and a case study of wind energy in China," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 227-244.
    21. Abdulelah Alkesaiberi & Fouzi Harrou & Ying Sun, 2022. "Efficient Wind Power Prediction Using Machine Learning Methods: A Comparative Study," Energies, MDPI, vol. 15(7), pages 1-24, March.
    22. Dai, Juchuan & Yang, Xin & Wen, Li, 2018. "Development of wind power industry in China: A comprehensive assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 156-164.
    23. Xia, Hui & Dai, Ling & Sun, Liping & Chen, Xi & Li, Yuening & Zheng, Yihan & Peng, Yanlai & Wu, Kaiya, 2023. "Analysis of the spatiotemporal distribution pattern and driving factors of renewable energy power generation in China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 414-428.
    24. Liu, Pihui & Han, Chuanfeng & Teng, Minmin, 2022. "Does clean cooking energy improve mental health? Evidence from China," Energy Policy, Elsevier, vol. 166(C).
    25. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    26. Liu, Fa & Sun, Fubao & Liu, Wenbin & Wang, Tingting & Wang, Hong & Wang, Xunming & Lim, Wee Ho, 2019. "On wind speed pattern and energy potential in China," Applied Energy, Elsevier, vol. 236(C), pages 867-876.
    27. Franke, Katja & Sensfuß, Frank & Deac, Gerda & Kleinschmitt, Christoph & Ragwitz, Mario, 2021. "Factors affecting the calculation of wind power potentials: A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    28. Wang, Yuxuan & Sun, Tianye, 2012. "Life cycle assessment of CO2 emissions from wind power plants: Methodology and case studies," Renewable Energy, Elsevier, vol. 43(C), pages 30-36.
    29. Xing, Peixue & Wang, Yanan & Ye, Tao & Sun, Ying & Li, Qiao & Li, Xiaoyan & Li, Meng & Chen, Wei, 2024. "Carbon emission efficiency of 284 cities in China based on machine learning approach: Driving factors and regional heterogeneity," Energy Economics, Elsevier, vol. 129(C).
    30. Saeed Khanagha & Mohammad Taghi Ramezan Zadeh & Oli R. Mihalache & Henk W. Volberda, 2018. "Embracing Bewilderment: Responding to Technological Disruption in Heterogeneous Market Environments," Journal of Management Studies, Wiley Blackwell, vol. 55(7), pages 1079-1121, November.
    31. Ren, Guorui & Liu, Jinfu & Wan, Jie & Guo, Yufeng & Yu, Daren, 2017. "Overview of wind power intermittency: Impacts, measurements, and mitigation solutions," Applied Energy, Elsevier, vol. 204(C), pages 47-65.
    32. Tang, Zi, 2015. "An integrated approach to evaluating the coupling coordination between tourism and the environment," Tourism Management, Elsevier, vol. 46(C), pages 11-19.
    33. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    34. Quan-Jing Wang & Wen-Zhi Li & Zhan-Yuan Gong & Jia-Yu Fu, 2025. "The Coupling and Coordination Between Digital Economy and Green Economy: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 61(3), pages 562-578, February.
    35. Jiang, Zihao & Liu, Zhiying, 2022. "Policies and exploitative and exploratory innovations of the wind power industry in China: The role of technological path dependence," Technological Forecasting and Social Change, Elsevier, vol. 177(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. Siyao Wang & Chongzhi Liu & Fu Chen, 2025. "Evaluation of Peak Shaving and Valley Filling Efficiency of Electric Vehicle Charging Piles in Power Grids," Energies, MDPI, vol. 18(19), pages 1-19, October.

    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. Li, Mengdi & Han, Chuanfeng & Meng, Lingpeng & Liu, Pihui & Shao, Zhiguo, 2025. "Spatiotemporal dynamics and driving factors of the coupling coordination between solar photovoltaic efficiency and installed capacity in China (2015–2023)," Renewable Energy, Elsevier, vol. 247(C).
    2. Li, Mengdi & Han, Chuanfeng & Meng, Lingpeng & Liu, Pihui, 2025. "Spatiotemporal dynamics and factors of renewable energy mismatch in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    3. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Peng, Hongsong & Zhang, Jinhe & Lu, Lin & Tang, Guorong & Yan, Bingjin & Xiao, Xiao & Han, Ya, 2017. "Eco-efficiency and its determinants at a tourism destination: A case study of Huangshan National Park, China," Tourism Management, Elsevier, vol. 60(C), pages 201-211.
    5. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    6. Liu, Zuankuo & Xin, Li, 2019. "Has China's Belt and Road Initiative promoted its green total factor productivity?——Evidence from primary provinces along the route," Energy Policy, Elsevier, vol. 129(C), pages 360-369.
    7. An, Qingxian & Tao, Xiangyang & Xiong, Beibei & Chen, Xiaohong, 2022. "Frontier-based incentive mechanisms for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 302(1), pages 294-308.
    8. Jingyan Fu & Artie W. Ng, 2021. "Scaling up Renewable Energy Assets: Issuing Green Bond via Structured Public-Private Collaboration for Managing Risk in an Emerging Economy," Energies, MDPI, vol. 14(11), pages 1-16, May.
    9. Hua, Ershi & Sun, Ruyi & Feng, Ping & Song, Lili & Han, Mengyao, 2024. "Optimizing onshore wind power installation within China via geographical multi-objective decision-making," Energy, Elsevier, vol. 307(C).
    10. Zheng, Huazhu & Lu, Jungang & He, Hongming & Wu, Yongjiao & He, Maofeng & Cheng, Dong & Yao, Zhengyu & Gomez, Christopher, 2025. "Quantifying spatial heterogeneity and driving mechanisms of water-energy-food coordination in the Yellow River Basin: A hybrid framework approach," Energy, Elsevier, vol. 334(C).
    11. Tianqun Xu & Ping Gao & Qian Yu & Debin Fang, 2017. "An Improved Eco-Efficiency Analysis Framework Based on Slacks-Based Measure Method," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    12. Cui, Qi & He, Ling & Han, Guoyi & Chen, Hao & Cao, Juanjuan, 2020. "Review on climate and water resource implications of reducing renewable power curtailment in China: A nexus perspective," Applied Energy, Elsevier, vol. 267(C).
    13. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    14. Chunhua Xin & Xiufeng Lai, 2022. "Does the Environmental Information Disclosure Promote the High-Quality Development of China’s Resource-Based Cities?," Sustainability, MDPI, vol. 14(11), pages 1-26, May.
    15. Dai, Zhifeng & Zhu, Haoyang, 2024. "Climate policy uncertainty and urban green total factor productivity: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    16. Zhang, Shijun & Zhang, Meng & Meng, Shouwei, 2024. "Corporate transaction costs and corporate green total factor productivity," Finance Research Letters, Elsevier, vol. 61(C).
    17. Lv, Furong & Tang, Haiping, 2025. "Assessing the impact of climate change on the optimal solar–wind hybrid power generation potential in China: A focus on stability and complementarity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    18. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    19. Shuangjie Li & Hongyu Diao & Liming Wang & Chunqi Li, 2021. "Energy Efficiency Measurement: A VO TFEE Approach and Its Application," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    20. Nikos Chatzistamoulou & Kostas Kounetas, 2023. "Tracing green growth through industrial resource efficiency patterns: The role of competitiveness and clean technologies," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(7), pages 4011-4026, October.

    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:eee:appene:v:396:y:2025:i:c:s0306261925010505. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.