2009 IEEE Power &Amp; Energy Society General Meeting 2009
DOI: 10.1109/pes.2009.5275320
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Efficient allocation of fault indicators in distribution circuits using fuzzy logic

Abstract: This paper evaluates the behavior related to the main variables that influence in the quantification of potential points for installation of fault indicators along electric power distribution feeders. Moreover, based on these behavioral characteristics, fuzzy inference systems are also used to estimate the best positions to allocate fault indicators, which take into account the distance in that a particular bus is in relation to more adjacent protection devices, load profile and short-circuit current levels of… Show more

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Cited by 8 publications
(3 citation statements)
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“…The cost effectiveness of the method is tested and verified afterwards. One of the first ideas for indirect approach is the fuzzy method [17], [18]. Instead of computing precise positions appropriate for installation of FPIs, the method provides the results in a form of a chart which shows the installation potential for each bus along the main feeder, which represents distance from the network substation to the farthest network bus [19].…”
Section: Methodsmentioning
confidence: 99%
“…The cost effectiveness of the method is tested and verified afterwards. One of the first ideas for indirect approach is the fuzzy method [17], [18]. Instead of computing precise positions appropriate for installation of FPIs, the method provides the results in a form of a chart which shows the installation potential for each bus along the main feeder, which represents distance from the network substation to the farthest network bus [19].…”
Section: Methodsmentioning
confidence: 99%
“…Nonlinear models which are reviewed in Section 1 have been proposed to optimize the FI placement problem, and heuristic algorithms have been used to solve it.…”
Section: Description and Formulation Of The Problemmentioning
confidence: 99%
“…One of the methods used for optimal placement of FIs is to use the fuzzy inference . Nejadfard‐jahromiet al used energy not supplied index and investment cost to create the objective function of the optimization problem and used the fuzzy clustering‐based genetic algorithm to solve the FI placement problem.…”
Section: Introductionmentioning
confidence: 99%