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Fast fault detection and classification based on a combination of wavelet singular entropy theory and fuzzy logic in distribution lines in the presence of distributed generations
Affiliation:1. Universidad Politecnica Salesiana, Calle Vieja 12-30 y Elia Liut, 010150, Cuenca, Ecuador;2. Instituto de Energía Eléctrica, Universidad Nacional de San Juan, San Juan, Argentina
Abstract:This paper proposes a new method of fault detection and classification in asymmetrical distribution systems with dispersed generation to detect islanding and perform protective action based on applying a combination of wavelet singular entropy and fuzzy logic. In this method, positive components of currents at common coupling points are decomposed to adjust detailed coefficients of wavelet transforms and singular value matrices, and expected entropy values are calculated via stochastic process. Indexes are defined based on the wavelet singular entropy in positive components and three phase currents to detect and classify the fault. This protection scheme is put forward for fault detection and is investigated in different types of faults such as single-phase to ground, double-phase to ground, three-phase to ground and line to line in distribution lines in the presence of distributed generations, and different locations of faults are verified when the distributed generation is connected to the utility. The major priority of the proposed protection scheme is its reduction in time (10 ms from the event inception) in distinguishing islanding and protection transmission lines in the presence of distributed generations.
Keywords:Distribution line  Fault detection  Fault classification  Wavelet transform  Wavelet singular entropy  Fuzzy logic
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