Article: Research on safety risk perception of electrochemical energy storage power station under the background of environmental sustainable development Journal: International Journal of Business Intelligence and Data Mining (IJBIDM) 2026 Vol.28 No.8 pp.36 - 54 Abstract: The current risks faced by electrochemical energy storage power plants are diversified and complex, resulting in high false alarm rates, false negative rate, and long time consumption of traditional methods. Therefore, a safety risk perception method of electrochemical energy storage power station under the background of environmental sustainable development has been proposed. Cluster analysis of multi-source risk indicator data using GMM to identify potential risk patterns; It calculates the weights of various indicators based on cloud models, screens key risk factors, and constructs a multi-level risk indicator system; by integrating real-time monitoring data with prior knowledge through Bayesian inference, dynamic risk probability updates and perception can be achieved. The experimental results show that the minimum false alarm rate of the proposed method is 2.86%, the minimum false negative rate is 2.78%, and the risk perception time varies between 0.3 s and 0.7 s, indicating high engineering application value. Inderscience Publishers - linking academia, business and industry through research

Title: Research on safety risk perception of electrochemical energy storage power station under the background of environmental sustainable development

Authors: DongLiang Deng; LiXin Yin

Addresses: Three Gorges Electric Power Co., Ltd., Wuhan, 430000, China ' Three Gorges Electric Power Co., Ltd., Wuhan, 430000, China

Abstract: The current risks faced by electrochemical energy storage power plants are diversified and complex, resulting in high false alarm rates, false negative rate, and long time consumption of traditional methods. Therefore, a safety risk perception method of electrochemical energy storage power station under the background of environmental sustainable development has been proposed. Cluster analysis of multi-source risk indicator data using GMM to identify potential risk patterns; It calculates the weights of various indicators based on cloud models, screens key risk factors, and constructs a multi-level risk indicator system; by integrating real-time monitoring data with prior knowledge through Bayesian inference, dynamic risk probability updates and perception can be achieved. The experimental results show that the minimum false alarm rate of the proposed method is 2.86%, the minimum false negative rate is 2.78%, and the risk perception time varies between 0.3 s and 0.7 s, indicating high engineering application value.

Keywords: background of environmental sustainable development; cloud model; electrochemical energy storage power station; safety risk perception; Bayesian inference.

DOI: 10.1504/IJBIDM.2026.153562

International Journal of Business Intelligence and Data Mining, 2026 Vol.28 No.8, pp.36 - 54

Received: 01 Jul 2025
Accepted: 09 Oct 2025
Published online: 14 May 2026 *

Title: Research on safety risk perception of electrochemical energy storage power station under the background of environmental sustainable development

Keep up-to-date