Power Prediction of Photovoltaic System using Neural Network Models

2019

Master's thesis Renewable Energy ENE500 - University of Agder 2019 This workconsidersa photovoltaic (PV)system installed on the rooftop of Agder Energi’s headquarters located at Kjøita, Kristiansand. The system includes three different types of solar PV modules; Suntech (multi-Si), Sharp (a-Si/μ-Si) and REC (multi-Si), that have a total installed DC capacity of 45 kWp. The system is grid-connected and instrumented for research and monitoring purposes.Artificial Neural Network(ANN)models were trained to obtain the lowest mean square error(MSE), by testing different configurations using a model-based trial and error approach. The modelconfigurations that gavethe lowest(MSE) wereused to predic…