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2016
DOI: 10.1049/iet-gtd.2015.0041
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Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods

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Cited by 137 publications
(81 citation statements)
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“…The GA is the most popular algorithm with an excellent rate of convergence in compared to other optimization algorithms such as metaheuristic algorithms and is usually implemented in protective relaying to solve nonlinear problem . The initiation is selected randomly, maximum number of generations is fixed at 1500, population size is equal to 500, mutation is 0.2, and crossover is 0.8.…”
Section: Proposed Method: New Quadrilateral Zone Settingmentioning
confidence: 99%
“…The GA is the most popular algorithm with an excellent rate of convergence in compared to other optimization algorithms such as metaheuristic algorithms and is usually implemented in protective relaying to solve nonlinear problem . The initiation is selected randomly, maximum number of generations is fixed at 1500, population size is equal to 500, mutation is 0.2, and crossover is 0.8.…”
Section: Proposed Method: New Quadrilateral Zone Settingmentioning
confidence: 99%
“…• Métodos de optimización: los nuevos desarrollos apuntan a la creación de hí-bridos entre las diferentes técnicas aquí tratadas, de manera que se permitan resolver el problema de ubicación (binario) y dimensionamiento (continuo), con el mínimo esfuerzo computacional (memoria y tiempo) [70].…”
Section: Investigaciones Futurasunclassified
“…A hybrid algorithm known as shuffled bat algorithm has been proposed in Yammani et al for placement and sizing problem with loading the line beyond 100 % . A combination of analytical and genetic algorithm has been used for multiple DG allocation to minimize the system loss. A DG selection index taking real power loss (RPL) and voltage stability condition to find out the site and a DG sizing formula used to determine the size have been addressed in Kayal et al A new sensitivity index has been defined in Gampa and Das based on voltage sensitivity and apparent load power, for siting and sizing of DGs considering average hourly load data.…”
Section: Introductionmentioning
confidence: 99%