Intelligent Smart Monitoring Systems for Photovoltaic Power Generators

Photovoltaic (PV) power systems have significantly received a lot of attention from electrical engineers in industrial fields for decades. This paper develops an intelligent monitoring technique against PV systems for timely detecting abnormality of it due to fault possibly occurring in practice by...

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Bibliographic Details
Published inInternational Information Institute (Tokyo). Information Vol. 19; no. 7A; p. 2687
Main Author Cho, Hyun Cheol
Format Journal Article
LanguageEnglish
Published Koganei International Information Institute 01.07.2016
Subjects
Decision making
Fault detection
Generators
Monitoring
Neural networks
Photovoltaic cells
Solar cells
Stochasticity
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Summary:Photovoltaic (PV) power systems have significantly received a lot of attention from electrical engineers in industrial fields for decades. This paper develops an intelligent monitoring technique against PV systems for timely detecting abnormality of it due to fault possibly occurring in practice by using neural networks theory and stochastic decision making approach. Firstly, we construct Fourier neural network model for representing dynamics of PV generators and derive its parameter learning algorithm from a stochastic optimization method. Next, a well-known general likelihood ratio test (GLRT) scheme is employed to establish decision making rules for our fault detection. Lastly, real-time experiment is carried out to prove reliability of the proposed fault detection methodology using a test-bed of PV generator systems.
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ISSN:1343-4500
1344-8994