The determined growth of PV power plants and the integration of residential building façades with solar modules have increased the demand for PV modules in the global market (Aghaei et al. 2015). With the growing
In this paper, 40 PV modules TSM-240 are used to form the 10 kWp PV plant, as shown in Fig. 1.Based on the above mathematical model of PV modules, the simulation model of the PV array is built in MATLAB/Simulink, as
Harsh outdoor operations may cause various abnormalities or faults of photovoltaic (PV) array, decrease the energy yield and lifespan, and even cause catastrophic events. Recently, many approaches have been successfully applied to the fault diagnosis for PV arrays.
Shading faults and abnormal aging faults lead to different multi-peak, step-like characteristics of the I-V and P-V curves of the entire PV array respectively, and a drop in V m, I m, and P m of the PV array.
Photovoltaic (PV) arrays have output characteristics such as randomness and intermittency, and faults can seriously affect the safe operation of the power system. In order to improve the comprehensive performance of the PV array fault diagnosis model, a new intelligent online fault monitoring method for PV arrays is proposed in this paper.
Therefore, an accurate and efficient method for diagnosing and locating faults in PV arrays is of great academic significance and value for maintaining the stable, efficient, and reliable operation of PV power generation systems [, , ]. Different faults have different characteristics and different degrees of influence.
Fault data samples are collected as the basis of PV array fault diagnosis and localization, and also as a guarantee for model training and learning, the reliability of data samples is crucial for PV array fault diagnosis.
This advanced approach offers accurate detection and classification of various types of faults, including partial shading anomalies open and short circuit faults, degradation of PV modules. It provides a comprehensive framework for effective fault diagnosis in PV arrays.