Quantitative study on low cost factors of rural energy based on optimal objective function mathematical model

Zenglin Ding; Wenxuan Liu; Xinyuan Mu; Yang Yu; Xiaohe Wan

doi:10.1117/12.2641097

17 May 2022 Quantitative study on low cost factors of rural energy based on optimal objective function mathematical model

Zenglin Ding, Wenxuan Liu, Xinyuan Mu, Yang Yu, Xiaohe Wan

Author Affiliations +

Proceedings Volume 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022); 122593V (2022) https://doi.org/10.1117/12.2641097
Event: 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing, 2022, Kunming, China

Abstract

On the premise of localization of village and town resources and clean and renewable energy, by decomposing the cost of rural energy system into economic cost and environmental cost, the quantitative evaluation model of low-cost elements of rural energy system is established. The environmental cost is based on the output of life cycle assessment inventory. With a 15-year cycle, twelve energy system schemes in three typical villages and towns in severe cold areas and cold areas in China are taken as examples for comprehensive cost comparison. From the quantitative analysis results, the energy system dominated by fossil fuels (coal and liquefied petroleum gas) has higher economic cost and higher environmental cost; the energy system based on straw and firewood has lower economic cost and higher environmental cost; the economic cost and environmental cost of the energy system based on straw gas and biogas are low, and the comprehensive cost per capita is less than 5000 yuan, which is the optimal scheme for the future rural energy system planning.

Citation Download Citation

Zenglin Ding, Wenxuan Liu, Xinyuan Mu, Yang Yu, and Xiaohe Wan "Quantitative study on low cost factors of rural energy based on optimal objective function mathematical model", Proc. SPIE 12259, 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), 122593V (17 May 2022); https://doi.org/10.1117/12.2641097

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KEYWORDS

Solar energy

Renewable energy

Pollution control

Combustion

Biogases

Mathematical modeling

Data conversion

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