Study on the key parameters affecting the flow characteristics of water in the underground reservoir of an abandoned mine pumped-storage power station
Source abstract
Abstract
In the context of the global transition to low-carbon energy systems, addressing the challenges posed by the intermittent nature of large-scale renewable energy sources and the repurposing of abandoned mine resources is crucial. Underground tunnel reservoirs, as vital components of pumped-storage power stations, require a comprehensive understanding of how the intrinsic characteristics of the tunnels influence water flow behavior to ensure operational efficiency and safety. This study identifies five key factors that affect water flow characteristics in tunnels. A hydraulic model of a pumped-storage power station in abandoned mines is employed, and a single-factor comparison method is utilized to investigate the flow velocity, static water pressure, and head loss in the underground reservoir under varying conditions. Furthermore, using the response surface methodology, a multi-factor analysis is conducted to assess the combined impact of three critical factors—inlet flow velocity, curvature, and slope—on head loss. The results indicate that the influence of these factors on head loss follows the order: curvature > slope > inlet flow velocity. This study provides valuable decision-making support for the transformation of underground spaces and the selection of tunnels for underground reservoirs in abandoned mine pumped-storage power station projects. It offers crucial insights to facilitate the transition of mining areas and the development of new energy storage industries.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Tailings Management and Properties · Mine drainage and remediation techniques · Karst Systems and Hydrogeology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
SHCCIG Shenmu Zhangjiamao Mining Co., Ltd. 1 , Shenmu 719399,
State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering, China University of Mining and Technology 2 , Xuzhou 221116,
Funding
National Key Research and Development Program of China
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