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Green Power Trade Behavior in China’s Renewable Portfolio Standard: An Evolutionary Game-Based System Dynamics Approach

Author

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  • Chunning Na

    (School of Physics & Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China)

  • Can Jin

    (School of Physics & Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China)

  • Huan Pan

    (School of Physics & Electronic-Electrical Engineering, Ningxia University, Yinchuan 750021, China)

  • Lixia Ding

    (Eco-Tech Research Institute, State Grid Ningxia Electric Power Co., Ltd., Yinchuan 750004, China)

Abstract

To promote the consumption of renewable energy (RE), in 2019, China introduced the Renewable Portfolio Standard (RPS) and adopted the weight of consumption responsibility to replace the quota index. This paper investigates the behavioral decisions of green power plants and power sales companies using evolutionary game theory. The results show that RPS becomes effective based on two rules: (1) the unit fine is higher than the transaction cost for power sales companies; and (2) the transaction prices of RE and Trade of Green Certificate (TGC) are greater than the unit transaction cost for green power plants. Taking Ningxia Hui Autonomous Region as an example, the scenario analysis method and a simple system dynamics model are employed to investigate the impact of fines on the green power trade behavior. With different fines, power sales companies are more sensitive than green power plants. These results provide some policy recommendations to promote the consumption of RE.

Suggested Citation

  • Chunning Na & Can Jin & Huan Pan & Lixia Ding, 2022. "Green Power Trade Behavior in China’s Renewable Portfolio Standard: An Evolutionary Game-Based System Dynamics Approach," Sustainability, MDPI, vol. 14(9), pages 1-12, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5155-:d:801411
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    3. Yue, Tingyi & Wang, Honglei & Li, Chengjiang & Hu, Yu-jie, 2024. "Optimization strategies for green power and certificate trading in China considering seasonality: An evolutionary game-based system dynamics," Energy, Elsevier, vol. 311(C).

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