Abstract
A new intelligent method is proposed to detect faults in the photovoltaic (PV) array. Usually, there is an obvious temperature difference between the fault PV module and the normal PV module. So, the temperature information of the PV modules is utilized to locate the fault in the PV array firstly. Then, the Artificial Neural Network (ANN) is applied to diagnosis the type of the fault. The current of maximum power point (Impp), the voltage of maximum power point (Vmpp) and the temperature of the PV modules are input parameters of the ANN. The output of the ANNunit is the result of the fault detection. Basic tests have been carried out in the simulated environment under both normal and fault conditions. The simulation results show that the outputs of the ANN are almost consistent with the expected value. It can be verified that the proposed method based on ANN can not only find the location of the fault but also determine the type of the fault.
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© 2012 Springer-Verlag Berlin Heidelberg
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Li, Z., Wang, Y., Zhou, D., Wu, C. (2012). An Intelligent Method for Fault Diagnosis in Photovoltaic Array. In: Xiao, T., Zhang, L., Ma, S. (eds) System Simulation and Scientific Computing. ICSC 2012. Communications in Computer and Information Science, vol 327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34396-4_2
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DOI: https://doi.org/10.1007/978-3-642-34396-4_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34395-7
Online ISBN: 978-3-642-34396-4
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