Forecasting PV module electrical degradation due to dust using ANNs and PSO techniques

Renewable energy comes from several sources. We are particularly interested in this work in photovoltaic energy (PV), one of the most promising in our country. This work is devoted to studying the modelisation and forecasting of the electrical performance of photovoltaic (PV) modules based on Artificial Neural Networks (ANN) and Particle Swarm Optimisation technique (PSO) under the influence of dust accumulation on the surface of solar PV. For evaluating the power produced by two PV modules, the KC 200 GT and the BP SX 3200, we have employed methods based on ANN-PSO, as a function of temperature and illumination. The results show the efficiency of determining the power generated by the two photovoltaic modules studied using the ANN-PSO approaches.