Research on Personal Risk Management and Control Model for Intrinsic Safety of Power Grid Enterprises

Jiapeng Chen (), Zhenghang Wu, Pengliang Li, Ye Tao and Gengbin Liu
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Jiapeng Chen: Guangdong Power Grid Co. Ltd., Jieyang Power Supply Bureau
Zhenghang Wu: Guangdong Power Grid Co. Ltd., Jieyang Power Supply Bureau
Pengliang Li: Guangdong Power Grid Co. Ltd., Jieyang Power Supply Bureau
Ye Tao: Guangdong Power Grid Co. Ltd., Jieyang Power Supply Bureau
Gengbin Liu: Guangdong Power Grid Co. Ltd., Jieyang Power Supply Bureau

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 534-542 from Springer

Abstract: Abstract Safe production is the basis for the smooth development of all work of power grid enterprises, and has played a great role in the development of power grid enterprises. However, there are great potential safety hazards in its production, which is easy to cause personal safety accidents. Intrinsic safety refers to the inherent function of equipment or technology, which can fundamentally prevent accidents. Therefore, a personal risk management and control model is established for the intrinsic safety of power grid enterprises. Analyze the intrinsic safety concept of power grid enterprises, establish the mathematical model of personal safety hazards, set the probability value of personal risk, and use the principal component analysis method to reduce the dimension to deal with the key factors of personal risk. On this basis, according to the personal risk management and control measures taken by the power grid enterprise’s intrinsic safety concept, a personal risk management and control model is constructed and solved by Pareto ant colony algorithm. The experimental results show that the proposed method can effectively improve the efficiency of personal risk management and control.

Keywords: Power grid enterprise; Personal risk; Intrinsic safety; Pareto ant colony algorithm; Risk control model; Principal component analysis (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-256-9_55

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