Electrical Engineering Department, South Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract
This paper presents a new method based on empirical mode decomposition and Hilbert transform for detecting islanding from non-islanding events in distributed generations. In this paper, the empirical mode decomposition is used to separate out intrinsic mode functions (IMF) from non-stationary power signal disturbance waveforms. Then, the Hilbert transform applied on all the IMFs to extract the instantaneous amplitude and frequency components. The required index is extracted from the energy spectrum density of the signals that introduced as U1, U2, and U3 and we can detect islanding events with high accuracy, low cost and high speed in distributed generations.
Doroozi, A., Olamaei, J. (2017). A New Passive Islanding Detection Method for Distributed Generations Using Time-Frequency Transform-Based EMD-HT. Signal Processing and Renewable Energy, 1(4), 9-25.
MLA
Abbas Doroozi; Javad Olamaei. "A New Passive Islanding Detection Method for Distributed Generations Using Time-Frequency Transform-Based EMD-HT". Signal Processing and Renewable Energy, 1, 4, 2017, 9-25.
HARVARD
Doroozi, A., Olamaei, J. (2017). 'A New Passive Islanding Detection Method for Distributed Generations Using Time-Frequency Transform-Based EMD-HT', Signal Processing and Renewable Energy, 1(4), pp. 9-25.
VANCOUVER
Doroozi, A., Olamaei, J. A New Passive Islanding Detection Method for Distributed Generations Using Time-Frequency Transform-Based EMD-HT. Signal Processing and Renewable Energy, 2017; 1(4): 9-25.
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