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Robust Method for Diagnosis and Detection of Faults in??Photovoltaic Systems Using Artificial Neural Networks
摘要： During their operation, PV systems can be subject of various faults and anomalies that could lead to a reduction in the effectiveness and the profitability of the PV systems. These faults can crash, cause a fire or stop the whole system. The main objective of this work is to present a sophisticated method based on artificial neural networks ANN for diagnosing; detecting and precisely classifying the fault in the solar panels in order to avoid a fall in the production and performance of the photovoltaic system. The work established in this paper intends in first place to propose a method to detect possible various faults in PV module using the Multilayer Perceptron (MLP) ANN network. The developed artificial neural network requires a large database and periodic training to evaluate the output parameters with good accuracy. To evaluate the accuracy and the performance of the proposed approach, a comparison is carried out with the classic method (the method of thresholding). To test the effectiveness of the proposed approach in detecting and classifying different faults, an extensive simulation is carried out using Matlab SIMULINK.
关键词： diagnosis,artificial neural networks,faults detection,photovoltaic system,method of thresholding
更新于2025-09-23 15:19:57
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[IEEE 2019 International Conference on Applied Automation and Industrial Diagnostics (ICAAID) - Elazig, Turkey (2019.9.25-2019.9.27)] 2019 International Conference on Applied Automation and Industrial Diagnostics (ICAAID) - An Intelligent Faults Diagnosis and Detection Method Based an Artificial Neural Networks for Photovoltaic Array
摘要： At present, renewable energy has many sources, most important of which are PV systems. It is therefore necessary to contribute to the diagnosis of the state of the photovoltaic system and the detection and diagnosis of malfunction. And identify and resolve failures in photovoltaic systems as quickly as possible, so that the system will operate at the expected levels of performance and reliability, thereby ensuring the expected return on investment. This article proposes modeling, detection and classification of photovoltaic system faults by Artificial neural network: ANN using measured values of the PV system voltage (v) and the current of the PV system (I). The method allows the classification of the PV state into several possible situations: normal operation and some different faults, modeling or simulations of MatLab. This method has proved to be able to detect and identify the faults in the PV array accurately and efficiently.
关键词： photovoltaic generator,Matlab / Simulink,artificial neural network,faults detection and diagnosis
更新于2025-09-16 10:30:52