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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Vydané v:Informatica (Ljubljana) Ročník 49; číslo 31; s. 1 - 9
Hlavný autor: Guo, Lei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Ljubljana Slovenian Society Informatika / Slovensko drustvo Informatika 01.09.2025
Predmet:
Algorithms
Blackouts
Climate change
Communication networks
Communications networks
Data collection
Data encryption
Data transmission
Disasters
Efficiency
Meteorological data
Natural disasters
Outages
Particle swarm optimization
Power failures
Prevention
Real time
Repair time
Resource allocation
Risk assessment
Sensors
Topology
Typhoons
Wireless communications
Wireless networks
ISSN:0350-5596, 1854-3871
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Shrnutí: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