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Energy conservation, environmental and economic value of the wind power priority dispatch in China

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  • Zhao, Xiaoli
  • Liu, Suwei
  • Yan, Fengguang
  • Yuan, Ziqian
  • Liu, Zhiwen

Abstract

n recent years, the annual curtailment ratio of wind power in China has been around 15%. Although the priority dispatch policy for wind power has been put in place in the country, it is not well implemented. One of the reasons for this is that wind power is viewed by some power system operators as “garbage power” due to its inherent intermittency nature. The improvement of social awareness of the value of wind power deployment is crucial for the effective implementation of the priority dispatch policy. In this paper, we analyze the impact of the priority dispatch of wind power on energy conservation and environmental improvement, and then compare the generation cost between wind power and coal-fired power while considering environmental externalities. We conclude that the energy intensity in the system decreases as the proportion of wind power generation increases, and the energy intensity is minimized when the proportion reaches 15%–20% provided a small amount of wind power curtailment is allowed. Meanwhile, we confirm that the wind power priority dispatch has significant positive impacts on environmental improvement. Further, we find that wind power generation cost is very close to coal-fired power cost when environmental cost is taken into account.

Suggested Citation

  • Zhao, Xiaoli & Liu, Suwei & Yan, Fengguang & Yuan, Ziqian & Liu, Zhiwen, 2017. "Energy conservation, environmental and economic value of the wind power priority dispatch in China," Renewable Energy, Elsevier, vol. 111(C), pages 666-675.
    • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:666-675
    DOI: 10.1016/j.renene.2017.03.032
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    Citations

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    Cited by:

    1. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
    2. Zhao, Xiaoli & Chen, Haoran & Liu, Suwei & Ye, Xiaomei, 2020. "Economic & environmental effects of priority dispatch of renewable energy considering fluctuating power output of coal-fired units," Renewable Energy, Elsevier, vol. 157(C), pages 695-707.
    3. Qingbin Yu & Yuliang Dong & Yanjun Du & Jiahai Yuan & Fang Fang, 2022. "Optimizing Operation Strategy in a Simulated High-Proportion Wind Power Wind–Coal Combined Base Load Power Generation System under Multiple Scenes," Energies, MDPI, vol. 15(21), pages 1-21, October.
    4. Jin, Jingliang & Zhou, Peng & Li, Chenyu & Bai, Yang & Wen, Qinglan, 2020. "Optimization of power dispatching strategies integrating management attitudes with low carbon factors," Renewable Energy, Elsevier, vol. 155(C), pages 555-568.
    5. Yao, Qi & Hu, Yang & Deng, Hui & Luo, Zhiling & Liu, Jizhen, 2020. "Two-degree-of-freedom active power control of megawatt wind turbine considering fatigue load optimization," Renewable Energy, Elsevier, vol. 162(C), pages 2096-2112.
    6. Yu, Shiwei & Zheng, Yali & Li, Longxi, 2019. "A comprehensive evaluation of the development and utilization of China's regional renewable energy," Energy Policy, Elsevier, vol. 127(C), pages 73-86.
    7. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Ruan, Yingjun, 2020. "Capacity credit and market value analysis of photovoltaic integration considering grid flexibility requirements," Renewable Energy, Elsevier, vol. 159(C), pages 908-919.
    8. Jingliang Jin & Qinglan Wen & Xianyue Zhang & Siqi Cheng & Xiaojun Guo, 2021. "Economic Emission Dispatch for Wind Power Integrated System with Carbon Trading Mechanism," Energies, MDPI, vol. 14(7), pages 1-17, March.
    9. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren & Söder, Lennart, 2018. "Analysis of wind power intermittency based on historical wind power data," Energy, Elsevier, vol. 150(C), pages 482-492.
    10. Li Han & Rongchang Zhang & Xuesong Wang & Yu Dong, 2018. "Multi-Time Scale Rolling Economic Dispatch for Wind/Storage Power System Based on Forecast Error Feature Extraction," Energies, MDPI, vol. 11(8), pages 1-27, August.
    11. Li, Tao & Li, Ang & Guo, Xiaopeng, 2020. "The sustainable development-oriented development and utilization of renewable energy industry——A comprehensive analysis of MCDM methods," Energy, Elsevier, vol. 212(C).
    12. Lu, Mengke & Guan, Jun & Wu, Huahua & Chen, Huizhe & Gu, Wei & Wu, Ye & Ling, ChengXiang & Zhang, Linqiang, 2022. "Day-ahead optimal dispatching of multi-source power system," Renewable Energy, Elsevier, vol. 183(C), pages 435-446.
    13. Sun, Jingqi & Ruze, Nuermaimaiti & Zhang, Jianjun & Shi, Jing & Shen, Boyang, 2021. "Capacity planning and optimization for integrated energy system in industrial park considering environmental externalities," Renewable Energy, Elsevier, vol. 167(C), pages 56-65.
    14. Cao, Jing & Ho, Mun S. & Ma, Rong & Zhang, Yu, 2024. "Transition from plan to market: Imperfect regulations in the electricity sector of China," Journal of Comparative Economics, Elsevier, vol. 52(2), pages 509-533.
    15. Jin, Jingliang & Wen, Qinglan & Cheng, Siqi & Qiu, Yaru & Zhang, Xianyue & Guo, Xiaojun, 2022. "Optimization of carbon emission reduction paths in the low-carbon power dispatching process," Renewable Energy, Elsevier, vol. 188(C), pages 425-436.
    16. Jin, Jingliang & Wen, Qinglan & Zhao, Liya & Zhou, Chaoyang & Guo, Xiaojun, 2023. "Measuring environmental performance of power dispatch influenced by low-carbon approaches," Renewable Energy, Elsevier, vol. 209(C), pages 325-339.

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