Islanding Detection Method of a Photovoltaic Power Generation System Based on a CMAC Neural Network

Kuei-Hsiang Chao, Min-Sen Yang and Chin-Pao Hung
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Kuei-Hsiang Chao: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Min-Sen Yang: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan
Chin-Pao Hung: Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 41170, Taiwan

Energies, 2013, vol. 6, issue 8, 1-18

Abstract: This study proposes an islanding detection method for photovoltaic power generation systems based on a cerebellar model articulation controller (CMAC) neural network. First, islanding phenomenon test data were used as training samples to train the CMAC neural network. Then, a photovoltaic power generation system was tested with the islanding phenomena. Because the CMAC neural network possesses association and induction abilities and characteristics that activate similar input signals in approximate memory during training process, the CMAC only requires that the weight values of the excited memory addresses be adjusted, thereby reducing the training time. Furthermore, quantification of the input signals enhanced the detection tolerance of the proposed method. Finally, the simulative and experimental data verified the feasibility of adopting the proposed detection method for islanding phenomena.

Keywords: cerebellar model articulation controller (CMAC); islanding phenomenon detection; photovoltaic (PV) 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: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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