A multimethod GIS-based framework for site selection of underground pumped storage power stations using closing coal mines: A case study of the Shanxi province, China
Zhongbo Sun,
Yixin Zhao,
Pascal Bolz,
Claire Côte and
Jiandong Ren
Renewable Energy, 2025, vol. 243, issue C
Abstract:
Underground Pumped Storage Power Stations (UPSPS) has the potential to convert underground coal mines into vital components of decentralized power supply systems. Geographic Information System (GIS) and Multi-Criteria Decision Making (MCDM) methods are applied to establish a two-phase framework for the site selection of UPSPS from a regional to local scale. Moreover, the two-phase method is tested in the Shanxi, the second largest coal producer in China. The results show that in this province, there are up to 6 locations that meet the feasibility assessment criteria and together, their theoretical potential storage capacity is 203.15 MWh. It is in Jincheng, a coal mine with a productivity of 0.9 Mt/a, a water head between the mine and a proximal water reservoir of 245 m, and the storage capacity of the system of 76.86 MWh, is the best location. Sensitivity and comparative analyses are conducted to verify the stability and reliability of the evaluation model. Although the ranking results are not the same, B1 and B4 (the negative height change pairs of the coal mine and proximal reservoir) are always prominent. This study outlines a method for cost-efficient, desktop-based site selection of UPSPS by integrating quantitative and qualitative data at different scales.
Keywords: Underground pumped storage power stations; Mine closure; Site selection; GIS; MCDM; Pythagorean fuzzy numbers (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148125001831
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:243:y:2025:i:c:s0960148125001831
DOI: 10.1016/j.renene.2025.122521
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().