2012
DOI: 10.1016/j.ijepes.2012.04.034
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An enhanced RCGA for a rapid and reliable load flow solution of electrical power systems

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Cited by 5 publications
(2 citation statements)
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“…The method developed in [32] is based on Mante Carlo simulation and have some inherited problems related result accuracy, computational burden and slow convergence. Recently a good attempt [33] has been made to improve the real coded GA method with bus reduction and sparsity technique but still convergence of the technique is not analyzed properly and is unreliable for online application.…”
Section: Introductionmentioning
confidence: 99%
“…The method developed in [32] is based on Mante Carlo simulation and have some inherited problems related result accuracy, computational burden and slow convergence. Recently a good attempt [33] has been made to improve the real coded GA method with bus reduction and sparsity technique but still convergence of the technique is not analyzed properly and is unreliable for online application.…”
Section: Introductionmentioning
confidence: 99%
“…A genetic algorithm is proposed for distribution system load flow by [15] and also used for integrated AC/DC system load flow in [16]. A real-coded genetic algorithm for load flow solution is proposed [17]. For the placement of various wind distributed generators, a power system optimization (PSO)-based probabilistic load flow model is proposed in [18].…”
mentioning
confidence: 99%