Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 5, Issue 4, Pages 1575-1583Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2013.2296598
Keywords
Discrete wavelet; distributed generation; islanding detection; machine learning; Procrustes analysis
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This paper presents a new approach based on wavelet design and machine learning applied to passive islanding detection of distributed generation. Procrustes analysis is used to determine the filter coefficients of a newly designed wavelet. To automate the classification process, machine learning algorithms are used to develop appropriate models. The IEEE 13-bus standard test distribution system simulated in PSCAD/EMTDC is used as a test bed to assess the performance of the proposed approach. The numerical results demonstrating the effectiveness of the proposed approach are discussed and conclusions are drawn.
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