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Long-Term Impacts of Carbon Tax and Feed-in Tariff Policies on China's Generating Portfolio and Carbon Emissions: A Multi-Agent-Based Analysis

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  • Lin-Ju Chen
  • Lei Zhu
  • Ying Fan
  • Sheng-Hua Cai

Abstract

Using agent-based modelling, this paper established an adaptive simulation model of China's wholesale electricity market with endogenous investment decisions and technical progress. The model took into account the heterogeneities of power generators, including emission reduction attitudes and risk appetites. Using this model, we simulated how carbon tax and feed-in tariff (FIT) policies will affect each single generator in terms of market behaviours (price bidding and investment) to explore the evolution of power generating portfolio and emissions differently in the time horizon 2010–2050. The validity of the model was tested according to China's electricity market data. We found that FIT for wind power and solar power will crowd out the investment in gas power and nuclear power, rather than replacing coal power. Compared to FIT, carbon tax is a more effective tool for emission abatement and incentivize multiple low carbon generating technologies. And optimal rate of carbon tax should be no more than 250 CNY/t CO 2 .

Suggested Citation

  • Lin-Ju Chen & Lei Zhu & Ying Fan & Sheng-Hua Cai, 2013. "Long-Term Impacts of Carbon Tax and Feed-in Tariff Policies on China's Generating Portfolio and Carbon Emissions: A Multi-Agent-Based Analysis," Energy & Environment, , vol. 24(7-8), pages 1271-1293, December.
  • Handle: RePEc:sae:engenv:v:24:y:2013:i:7-8:p:1271-1293
    DOI: 10.1260/0958-305X.24.7-8.1271
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    2. Foramitti, Joël & Savin, Ivan & van den Bergh, Jeroen C.J.M., 2021. "Emission tax vs. permit trading under bounded rationality and dynamic markets," Energy Policy, Elsevier, vol. 148(PB).
    3. Lin-Ju Chen & Zhen-Hai Fang & Fei Xie & Hai-Kuo Dong & Yu-Heng Zhou, 2020. "Technology-side carbon abatement cost curves for China’s power generation sector," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1305-1323, October.
    4. Chen, Huadong & Wang, Can & Cai, Wenjia & Wang, Jianhui, 2018. "Simulating the impact of investment preference on low-carbon transition in power sector," Applied Energy, Elsevier, vol. 217(C), pages 440-455.

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