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Multi-Agent-Based Fault Location and Cyber-Attack Detection in Distribution System

doi: 10.3390/en16010224
Accurate fault location is challenging due to the distribution network’s various branches, complicated topology, and the increasing penetration of distributed energy resources (DERs). The diagnostics for power system faults are based on fault localization, isolation, and smart power restoration. Adaptive multi-agent systems (MAS) can improve the reliability, speed, selectivity, and robustness of power system protection. This paper proposes a MAS-based adaptive protection mechanism for fault location in smart grid applications. This study developed a novel distributed intelligent-based multi-agent prevention and mitigation technique for power systems against electrical faults and cyber-attacks. Simulation studies are performed on a platform constructed by interconnecting the power distribution system of Kenitra city developed in MATLAB/SIMULINK and the multi-agent system implemented in the JADE platform. The simulation results demonstrate the effectiveness of the proposed technique.
- Majmaah University Saudi Arabia
- University of Central Asia Kyrgyzstan
- Universite Moulay Ismail De Meknes Morocco
- Majmaah University Saudi Arabia
- University of Central Asia Kyrgyzstan
Technology, T, fault location; multi-agent systems; cyber-attacks; smart grid, fault location, multi-agent systems, cyber-attacks, smart grid
Technology, T, fault location; multi-agent systems; cyber-attacks; smart grid, fault location, multi-agent systems, cyber-attacks, smart grid
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).9 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
