Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27–29, 2023, Tianjin, China

Research Article

A Power Generation Side Energy Storage Power Station Evaluation Strategy Model Based on the Combination of AHP and EWM to Assign Weight

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  • @INPROCEEDINGS{10.4108/eai.27-10-2023.2341927,
        author={Chunyu  Hu and Chunlei  Shen and Yifan  Zhou and Zezhong  Kang},
        title={A Power Generation Side Energy Storage Power Station Evaluation Strategy Model Based on the Combination of AHP and EWM to Assign Weight},
        proceedings={Proceedings of the 4th International Conference on Economic Management and Big Data Applications, ICEMBDA 2023, October 27--29, 2023, Tianjin, China},
        publisher={EAI},
        proceedings_a={ICEMBDA},
        year={2024},
        month={1},
        keywords={ahp; entropy weight method; evaluation system; energy storage power station},
        doi={10.4108/eai.27-10-2023.2341927}
    }
    
  • Chunyu Hu
    Chunlei Shen
    Yifan Zhou
    Zezhong Kang
    Year: 2024
    A Power Generation Side Energy Storage Power Station Evaluation Strategy Model Based on the Combination of AHP and EWM to Assign Weight
    ICEMBDA
    EAI
    DOI: 10.4108/eai.27-10-2023.2341927
Chunyu Hu1, Chunlei Shen1, Yifan Zhou1, Zezhong Kang2,*
  • 1: State Grid Integrated Energy Service Group CO.LTI
  • 2: North China Electric Power University
*Contact email: kangzezhong610@163.com

Abstract

With the strong support of national policies towards renewable energy, the rapid proliferation of energy storage stations has been observed. In order to provide guidance for the operational management and state monitoring of these energy storage stations, this paper proposes an evaluation framework for such facilities. Departing from the dimensions of adjustment capacity and operational proficiency, an applicability assessment model for electric energy storage technology is constructed. The model structure is hierarchically organized into goal layer, criterion layer, indicator layer, and alternative layer. Grounded on foundational data from the indicator layer, a combination of Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) is employed to compute indicator weights and relationship matrices. Independent evaluations and comprehensive assessments for distinct criteria are undertaken, culminating in the determination of applicability assessment outcomes for different strategies. These outcomes hold substantial implications for the planning, policy formulation, and commercial utilization of electric energy storage, rendering this research a pivotal reference.