Detection and Diagnosis in Photovoltaic Panels Using Artificial Intelligence Techniques Based on Random Forest and LSTM Neural Networks
This paper investigates the use of artificial intelligence techniques for monitoring photovoltaic systems and for fault detection and diagnosis. The proposed methodology uses approximately 1.37 million records collected over 16 days, including electrical variables, such as the voltage and DC current of the two photovol...