Evaluation of the Influencing Factors of Using Underground Space of Abandoned Coal Mines to Store Hydrogen Based on the Improved ANP Method

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Abstract

Storage is currently a major obstacle to the promotion of hydrogen energy. Hydrogen storage in abandoned coal mines can achieve the effective use of underground space while meeting the growing demand for energy storage facilities, which can bring economic and environmental benefits. However, research in this area has been limited to the conceptual discussion stage, without establishing a scientific evaluation method for the potential of modifying and utilizing abandoned coal mine space. In this study, based on the analytic network process (ANP), the Apriori algorithm is introduced to mine the association rules for various influencing factors. First, the Apriori algorithm is applied to mine association rules between indicators, eliminate unnecessary influence relationships, simplify the network structure model, and optimize the ANP weight calculation results; second, the solution method of judgment matrix is improved with triangular fuzzy numbers, and the index weight is solved by fuzzy nine marks instead of the method of nine scale, which is convenient for experts to give the fuzzy scale while better reflecting the opinions of experts. Finally, the ANP algorithm is applied to rank the weights of the obtained influencing factors, discuss the main factors with higher weights, and analyze the feasibility of converting candidate coal mines into hydrogen storage facilities using the derived evaluation method in the case study. The evaluation methods and conclusions presented in this study provide analytical tools and a decision basis for analyzing the feasibility of converting underground space of abandoned coal mines into hydrogen storage facilities and assessing the economic indicators.

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APA

Liu, W., & Pei, P. (2021). Evaluation of the Influencing Factors of Using Underground Space of Abandoned Coal Mines to Store Hydrogen Based on the Improved ANP Method. Advances in Materials Science and Engineering, 2021. https://doi.org/10.1155/2021/7506055

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