2020 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD) 2020
DOI: 10.1109/asemd49065.2020.9276231
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Optimal Allocation of Fault Current Limiter in Distribution Network with NSGA-II Algorithm

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Cited by 2 publications
(2 citation statements)
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“…The proposed algorithm is employed on the optimal distribution of flexible fault current limiters and applied to the revised IEEE 33-BUS distribution systems with distributed generation and IEEE 30-BUS benchmark system. The proposed method produced optimal configuration of the system and displayed an improved accuracy when compared to a non-dominated sorting genetic algorithm, as well as a Multi Objective Particle Swarm Optimization which are shown in [121] and [122] respectively. However, the algorithm was not compared to the conventional BA.…”
Section: A Review Of Various Swarm-based Motmentioning
confidence: 99%
“…The proposed algorithm is employed on the optimal distribution of flexible fault current limiters and applied to the revised IEEE 33-BUS distribution systems with distributed generation and IEEE 30-BUS benchmark system. The proposed method produced optimal configuration of the system and displayed an improved accuracy when compared to a non-dominated sorting genetic algorithm, as well as a Multi Objective Particle Swarm Optimization which are shown in [121] and [122] respectively. However, the algorithm was not compared to the conventional BA.…”
Section: A Review Of Various Swarm-based Motmentioning
confidence: 99%
“…In [14], the Pareto optimal solution set of resistive-type FCLs are obtained by using an improved multi-objective particle swarm optimization (MOPSO) and a multi-objective artificial bee colony. In [15], a nondominated sorting genetic algorithm (NSGA-II) is applied to optimize the allocation of DGs and FCLs to reduce fault negative effects on distribution networks. Based on the decomposition strategy, a multi-objective evolutionary algorithm is used to improve the reliability and fault current reduction in [16].…”
Section: Introductionmentioning
confidence: 99%