期刊
SUSTAINABLE CITIES AND SOCIETY
卷 81, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scs.2022.103837
关键词
Urban Integrated Energy System; Best-worst Method; CRITIC; Plan Selection; Multi-criteria Decision-making
资金
- China Postdoctoral Science Foundation [2021M691231]
- Fundamental Research Funds for the Central Universities [21621043]
- GuangDong Basic and Applied Basic Research Foundation [2021A1515110295]
- Guangzhou Social Science Planning Leading Group Office [2021GZYB03]
This paper proposes an innovative intuitionistic fuzzy framework for the selection of urban integrated energy system plans, which includes a comprehensive evaluation index system and a combined weighting method. The proposed framework is validated using a case study of UIES in Shanghai, and the results indicate the significant influence of initial investment, renewable energy utilization rate, and comprehensive utilization rate on plan selection.
An applicable and scientific plan of integrated energy system is conducive to the improvement of system operation efficiency and project investment profits. Different from the industrial park integrated energy system, the urban integrated energy system (UIES) is more closed to residents' life with limited available energy resources, and concern more about energy efficiency and environmental protection characteristics. However, there are few studies focusing on plan selection of UIES investment or considering UIES actual requirements. Therefore, this paper innovatively proposes an intuitionistic fuzzy framework for UIES plan selection. Firstly, based on project demands and characteristics, a comprehensive evaluation index system is constructed from 4 dimensions of economic cost, energy utilization, environmental impact and social recognition. Secondly, under the consideration of method characteristics and calculation rules, a novel combined weighting method integrating the Best-worst Method and the CRITIC are proposed to determine index weights. Thirdly, drawing a balance between group utility and individual regret, decision-making information is aggregated and alternative plans are sorting. Lastly, a case of UIES in Shanghai is applied to verify the proposed framework. Results show that the initial investment, the utilization rate of renewable energy, and the comprehensive utilization rate have the greatest influence on UIES plan selection.
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