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• W2801352202 startingPage "e2602" @default.
• W2801352202 abstract "Integration of the distributed generators into a distribution system encounters various system issues, and out of those islanding detection is 1 of the major protection problems to focus on. Many detection schemes have been proposed in the recent past, which possess a nondetection zone (NDZ) and usually neglect to provide a justification for the selected detecting features among all possible measures. Sensitive feature selection and minimization of NDZ are the 2 major objectives of this study. This paper comprises of 2 operational modes of designed IEEE 13-bus test feeder (offline mode and online mode of operation). The offline mode of system operation focuses on selecting the optimal feature vectors using the proposed “modified multiobjective differential evolution algorithm” coupled with an extreme learning machine classifier. The modified multiobjective differential evolution algorithm-extreme learning machine is applied to find out 2 optimum feature vectors, one by considering accuracy and minimal features and another one by dependability with a single feature as its objective functions. The online mode concentrates on the proposed new hybrid islanding detection method comprised of both passive and active detection techniques. Passive technique implements a decision tree designed by using the obtained accuracy-based feature vector. Decision tree triggers the active method on suspecting the runtime instances as non-islanding events to reduce the NDZ. Active method uses the obtained dependability-based feature vector as an injecting parameter. The test results indicate the efficiency and accuracy of the proposed approach under different circumstances of power mismatch." @default.
• W2801352202 created "2018-05-17" @default.
• W2801352202 creator A5014465654 @default.
• W2801352202 creator A5081439630 @default.
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• W2801352202 date "2018-05-07" @default.
• W2801352202 modified "2023-10-12" @default.
• W2801352202 title "Hybrid islanding detection with optimum feature selection and minimum NDZ" @default.
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• W2801352202 doi "https://doi.org/10.1002/etep.2602" @default.
• W2801352202 hasPublicationYear "2018" @default.
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