Low-carbon economic dispatch strategy for integrated power system based on the substitution effect of carbon tax and carbon trading
Tiancheng Ouyang,
Yinxuan Li,
Shutao Xie,
Chengchao Wang and
Chunlan Mo
Energy, 2024, vol. 294, issue C
Abstract:
As the introduction of carbon peak and carbon neutrality, the intensity of carbon regulation is growing. The power system, as the main body of carbon emission, will face the constraints of compound carbon reduction policy. To address this issue, a low-carbon economic dispatch strategy for integrated power system based on the substitution effect of carbon tax and carbon trading is proposed to improve the economic and environmental joint benefits. Firstly, facing the volatility characteristics of carbon trading price, Monte Carlo method is implemented to analyze the uncertainty of carbon trading price. Next, the renewable energy power and electricity load are forecast by long short-term memory method. Subsequently, the gray wolves algorithm is imposed to optimize the dispatch model and obtain the optimal dispatch plan. The comparative analysis reveals that the carbon emission and dynamic payback period of the optimized integrated power system are 4.37 × 106 t and 10.06 years, which are reduced 1.67 × 105 t and 0.3 years compared with the conventional power system. Besides, the economic analysis demonstrates that the substitution effect can decrease the unit cost of carbon emission by 1.03 USD/t. Finally, the comparative analysis manifests that the proposed dispatch model can effectively boost the economic and environmental joint benefits for the integrated power system.
Keywords: Integrated power system; Substitution effect; Stepped carbon tax; Carbon price uncertainty; Gray wolves algorithm (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:294:y:2024:i:c:s0360544224007321
DOI: 10.1016/j.energy.2024.130960
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