A new islanding detection scheme based on combination of slantlet transform and probabilistic neural network for grid-tied photovoltaic system

Citation

Ahmadipour, Masoud and Giyoev, Borbad M. and Hizam, Hashim (2019) A new islanding detection scheme based on combination of slantlet transform and probabilistic neural network for grid-tied photovoltaic system. In: 1st IEEE 2019 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE 2019), 14-15 Mar. 2019, Moscow, Russia. .

Abstract

According to find islanding in a grid tied photovoltaic system, a combination of Slantlet Transform (SLT) and Probabilistic Neural Network (PNN) has been proposed in this paper. The SLT is used to extract the unique features from three phase voltage signals at the Point of Common Coupling (PCC). The produced features vector is fed to a probabilistic neural network classifier as input pattern which is used to predict islanding condition. The proposed technique is validated through comparing with islanding response time in different situations with the offered response time through Rate of Change of Frequency (ROCOF) method.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/REEPE.2019.8708802
Publisher:	IEEE
Keywords:	Detect islanding technique; Photovoltaic systems; SLT; PNN
Depositing User:	Nabilah Mustapa
Date Deposited:	15 Jun 2020 07:48
Last Modified:	15 Jun 2020 07:48
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/REEPE.2019.8708802
URI:	http://psasir.upm.edu.my/id/eprint/36330
Statistic Details:	View Download Statistic

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