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- W1508406118 abstract "The main purpose of this paper is to propose an intelligent fault diagnostic method for photovoltaic (PV) systems. First, Solar Pro software package was used to simulate a photovoltaic system for gathering power generation data of photovoltaic modules during normal operations and malfunctions. Then, the collected power generation data was used to construct matter-element models based on extension theory for PV systems. The matter-element model combines with the neural networks to form an intelligent fault diagnosis system for PV systems. The proposed fault diagnosis method was adopted to identify the faulty types of a 3.15kW PV system. The simulation results indicate that the proposed fault diagnosis method can detect the malfunction types of PV system rapidly and accurately with less time and memory consumption." @default.
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- W1508406118 date "2010-01-01" @default.
- W1508406118 modified "2023-10-01" @default.
- W1508406118 title "A Novel Fault Diagnosis Method Based-on Modified Neural Networks for Photovoltaic Systems" @default.
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- W1508406118 doi "https://doi.org/10.1007/978-3-642-13498-2_69" @default.
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