2020
DOI: 10.1007/s12065-020-00364-1
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Optimal UPQC location in power distribution network via merging genetic and dragonfly algorithm

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Cited by 6 publications
(1 citation statement)
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“…Optimization models implemented to determine the location of the UPQC must offer more reliability and feedback signals. Some hybrid algorithms have been used to determine the optimal location of the UPQC by focusing on efficiency, system cost, and voltage stability index such as a hybrid algorithm of the genetic algorithm and dragonfly algorithm (DA) known as the genetically modified DA algorithm [152] and crow search mating-based lion algorithm [153]. In [154], a novel rider optimization algorithm (ROA)-modified PSO on a fitness basis is presented for the improvement of PQ by choosing a particular location and size for the UPQC.…”
Section: Upqc Location In the Distribu-tion Networkmentioning
confidence: 99%
“…Optimization models implemented to determine the location of the UPQC must offer more reliability and feedback signals. Some hybrid algorithms have been used to determine the optimal location of the UPQC by focusing on efficiency, system cost, and voltage stability index such as a hybrid algorithm of the genetic algorithm and dragonfly algorithm (DA) known as the genetically modified DA algorithm [152] and crow search mating-based lion algorithm [153]. In [154], a novel rider optimization algorithm (ROA)-modified PSO on a fitness basis is presented for the improvement of PQ by choosing a particular location and size for the UPQC.…”
Section: Upqc Location In the Distribu-tion Networkmentioning
confidence: 99%