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Analysis of wind power generation operation management risk in China

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  • Li, Cun-bin
  • Li, Peng
  • Feng, Xia

Abstract

The Chinese government has made an important effort to diversify the country's energy mix and exploit different sources of renewable energy. Although China's installed wind power capacity has undergone a dramatic expansion over the past six years, the electricity generated from wind power has not increased as expected. Meanwhile, operational risks, such as high generation cost, mismatch between capacity and generation, intermittent wind power generation, power grid construction lag, deficient policy, and operation mechanism, have become increasingly prominent. If not controlled, these risks will negatively affect wind power development in China. Therefore, this paper established a quantitative analysis model of wind power operation management risk from two aspects, feed-in tariff and grid electricity (electricity being connected to the grid), based on an analysis of wind power operation management risk in China. Moreover, this study quantitatively assessed the risk of the operational management of a wind farm in Inner Mongolia. Finally, corresponding risk control strategies for the healthy development of wind power generation in China were proposed.

Suggested Citation

  • Li, Cun-bin & Li, Peng & Feng, Xia, 2014. "Analysis of wind power generation operation management risk in China," Renewable Energy, Elsevier, vol. 64(C), pages 266-275.
    • Handle: RePEc:eee:renene:v:64:y:2014:i:c:p:266-275
    DOI: 10.1016/j.renene.2013.11.055
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    References listed on IDEAS

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    Cited by:

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    2. Al-Nory, Malak & El-Beltagy, Mohamed, 2014. "An energy management approach for renewable energy integration with power generation and water desalination," Renewable Energy, Elsevier, vol. 72(C), pages 377-385.
    3. Wu, Zhongqun & Sun, Hongxia, 2015. "Behavior of Chinese enterprises in evaluating wind power projects: A review based on survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 133-142.
    4. Liang, Yuanyuan & Yu, Biying & Wang, Lu, 2019. "Costs and benefits of renewable energy development in China's power industry," Renewable Energy, Elsevier, vol. 131(C), pages 700-712.
    5. Diógenes, Jamil Ramsi Farkat & Claro, João & Rodrigues, José Coelho, 2019. "Barriers to onshore wind farm implementation in Brazil," Energy Policy, Elsevier, vol. 128(C), pages 253-266.
    6. Wu, Zhongqun & Yang, Chan & Zheng, Ruijin, 2022. "Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid," Energy, Elsevier, vol. 245(C).
    7. Zeinalnezhad, Masoomeh & Chofreh, Abdoulmohammad Gholamzadeh & Goni, Feybi Ariani & Hashemi, Leila Sadat & Klemeš, Jiří Jaromír, 2021. "A hybrid risk analysis model for wind farms using Coloured Petri Nets and interpretive structural modelling," Energy, Elsevier, vol. 229(C).
    8. Fan, Zhi-Ping & Cai, Siqin & Guo, Dongliang & Xu, Bo, 2022. "Facing the uncertainty of renewable energy production: Production decisions of a power plant with different risk attitudes," Renewable Energy, Elsevier, vol. 199(C), pages 1237-1247.
    9. Zhou, Shan & Yang, Pu, 2020. "Risk management in distributed wind energy implementing Analytic Hierarchy Process," Renewable Energy, Elsevier, vol. 150(C), pages 616-623.
    10. Wenjin Li & Bingkang Li & Rengcun Fang & Peipei You & Yuxin Zou & Zhao Xu & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Enterprise Related to Electricity Transmission and Distribution Tariff Regulation Employing a Hybrid MCDM Model," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
    11. Fan, Xiao-chao & Wang, Wei-qing & Shi, Rui-jing & Li, Feng-ting, 2015. "Review of developments and insights into an index system of wind power utilization level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 463-471.

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