An Effective Method for Islanding Detection Based on Variational Mode Decomposition

Year 2019, Volume: 19 Issue: 2, 135 - 145, 01.07.2019

Solgun Salimi Amangaldi Koochaki

Abstract

DOI: 10.26650/electrica.2019.19007

The present study presents a new islanding
detection method based on variational mode decomposition (VMD). In the method,
the VMD transform of the voltage at point of common coupling is calculated, and
then based on the decomposed modes, an islanding detection index for
distinguishing between islanding and normal conditions will be derived.
Pursuing this objective, the measured voltage is decomposed into four modes,
and a new islanding detection index will be derived from their energy and their
variations. Then, thresholds will be adjusted based on values of proposed index
in various conditions on normal and islanding operations. The proposed
algorithm decomposes the measured signal into a predetermined number of
intrinsic modes around central frequencies; the method is insensitive to the
noise and sampling frequency. To validate the method, a distribution network
has been simulated in PSCAD/EMTDC, and the algorithm is tested on a variety of
islanding and normal circumstances. The results illustrate desired performance
of the proposed algorithm for conditions such as motor, nonlinear, and large
load switching; as normal condition; and islanding condition with a variety of
power mismatches between local load and distributed generation. The results
demonstrate the desired performance of the method with respect to both speed
and accuracy.

Cite this article as: Salimi S, Koochaki A.
An Effective Method for Islanding Detection Based on Variational Mode
Decomposition. Electrica, 2019; 19(2): 135-1145.

Keywords

Passive islanding detection, Variational mode decomposition, Energy modes, Threshold, Non-detection zone

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• Solgun Salimi was born in 1981; received the B.Sc in electrical engineering from the Faculty of Electrical Engineering, k. N. Toosi University, Iran, in 2003; she received M.Sc from Aliabad Katoul Branch of Islamic Azad University, Iran, in 2017. Her research interests are power system analysis, islanding detection algorithms.
• Amangaldi Koochaki was born in 1981; received the B.Sc in electrical engineering from the Faculty of Electrical Engineering, University of Tehran, Iran, in 2003; he received M.Sc and Ph.D from Amirkabir University of Technology, Iran, in 2003 and 2010 respectively. Now he is assistant professor in Aliabad Katoul branch of Islamic Azad University, Iran. His research interests are power system analysis, relay coordination and renewable energies.