Power Grid Comprehensive Disaster Prevention and Mitigation Management System Based on Wireless Communication Network

With the continuous expansion of the power grid scale and frequent natural disasters, it is urgent to develop an efficient power grid comprehensive disaster prevention and mitigation management system. Based on wireless communication networks, this paper proposes an adaptive risk assessment and reso...

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Bibliographic Details
Published in:Informatica (Ljubljana) Vol. 49; no. 31; pp. 1 - 9
Main Author: Guo, Lei
Format: Journal Article
Language:English
Published: Ljubljana Slovenian Society Informatika / Slovensko drustvo Informatika 01.09.2025
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ISSN:0350-5596, 1854-3871
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Summary:With the continuous expansion of the power grid scale and frequent natural disasters, it is urgent to develop an efficient power grid comprehensive disaster prevention and mitigation management system. Based on wireless communication networks, this paper proposes an adaptive risk assessment and resource allocation algorithm (ARARA). The algorithm integrates real-time meteorological data, power grid topology and equipment status information, uses weighted average fusion and other algorithms to process multi-source data, uses the gradient descent method to realise the dynamic adjustment of risk assessment model parameters, and accurately predicts the potential disaster risk of the power grid. In the resource allocation link, the particle swarm optimisation algorithm is improved, and constraints such as resource quantity and repair time are comprehensively considered to allocate repair resources to minimise power outage losses and maximise resource utilisation efficiency. The experimental simulation uses actual power grid data from a local grid operator to validate the effectiveness of ARARA in real-world scenarios. The results show that the risk assessment accuracy of the ARARA algorithm reaches 92%, which is 15% higher than that of traditional algorithms; it can reduce power outage losses by 30% and increase resource utilisation by 25%, opening up a new path for power grid disaster prevention and mitigation management.
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ISSN:0350-5596
1854-3871
DOI:10.31449/inf.v49i31.9290