Energy Generation Forecasting for Solar PV and Hybrid Solar PV & BESS Using System Advisor Model

Energy generation forecasting is critical for enhancing the performance and economic viability of renewable energy systems. This study utilizes the System Advisor Model (SAM) to forecast energy generation for two configurations: Solar Photovoltaic (PV) systems and hybrid Solar battery energy Storage Systems (BESS). The solar PV system with 500kW AC capacity and hybrid PV & BESS of 500kW AC (PV) and 250kWh BESS is considered for this work. The datasets are generated for energy generation from the System Advisor Model (SAM) by taking 8760 samples. The forecasting algorithms like Linear regression (LR) and Random Forest (RF) are applied to compute the root means square error (RMSE) and mean square error (MSE) for the proposed system. A study for solar PV and hybrid PV & BESS is performed, modelled and simulated for location 23.2156 degrees N, 72.6369 degrees E, Gandhinagar, the capital city of Gujarat state, India. The results confirm the effectiveness and accuracy of the algorithm and prediction values for the next five years.