An Anti-Islanding Protection Technique Using a Wavelet Packet Transform and a Probabilistic Neural Network

Masoud Ahmadipour, Hashim Hizam, Mohammad Lutfi Othman and Mohd Amran Mohd Radzi
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Masoud Ahmadipour: Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Hashim Hizam: Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Mohammad Lutfi Othman: Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Mohd Amran Mohd Radzi: Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia

Energies, 2018, vol. 11, issue 10, 1-31

Abstract: This paper proposes a new islanding detection technique based on the combination of a wavelet packet transform (WPT) and a probabilistic neural network (PNN) for grid-tied photovoltaic systems. The point of common coupling (PCC) voltage is measured and processed by the WPT to find the normalized Shannon entropy (NSE) and the normalized logarithmic energy entropy (NLEE). Subsequently, the yield feature vectors are fed to the PNN classifier to classify the disturbances. The PNN is trained with different spread factors to obtain better classification accuracy. For the best performance of the proposed method, the precise analysis is done for the selection of the type of input data for the PNN, the type of mother wavelet, and the required transform level which is based on the accuracy, simplicity, specificity, speed, and cost parameters. The results show that, by using normalized Shannon entropy and the normalized logarithmic energy entropy, not only it offers simplicity, specificity and reduced costs, it also has better accuracy compared to other smart and passive methods. Based on the results, the proposed islanding detection technique is highly accurate and does not mal-operate during islanding and non-islanding events.

Keywords: islanding detection; wavelet packet transform; probabilistic neural network; symmetrical and asymmetrical faults; photovoltaic system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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