Simulation modeling and analysis of carbon emission reduction potential of multi-energy generation

Dongfang Ren and Xiaopeng Guo ()
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Dongfang Ren: North China Electric Power University
Xiaopeng Guo: North China Electric Power University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 10, No 50, 11823-11845

Abstract: Abstract The carbon emission of the energy industry is mainly generated by power generation. Adjusting the power generation structure of multiple energy sources, so as to control the carbon emission of the power generation industry and measure its emission reduction space, is the key for power generation industry to achieve the goal of "dual carbon targets." This study develops a regional multi-energy generation simulation model, which is based on the core algorithm of generation dispatching approach. The established model can simulate the dispatching of all types of generating units in the region and output the data of power generation and emissions. Considering taking Shanxi Province as example, the output results under the benchmark scenario are obtained to verify the efficiency of the model. The error of renewable energy generation and other generation is less than 4%, which shows that the model has enough credibility. The results of the scenario analysis show that every 5% increase in the utilization rate of wind turbine units will increase almost 20% of the renewable energy power generation, reduce almost 15% of the thermal power and reduce at least 10% of the CO2 emissions. This proves that China's regional power generation industry has certain emission reduction potential. The proposed model has important application value for energy conservation and emission reduction of regional power generation industry.

Keywords: Power generation; Emission reduction potential; Multi-agent simulation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02556-4

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