Photovoltaic power generation forecasting utilizing long short term memory

This study develops and validates a short-term PV power forecasting model by using the combination of a genetic algorithm (GA) and Long Short Term Memory (LSTM). The performance of the proposed model is compared with LSTM baseline model by three errors (Root mean square error(RMSE), Mean absolute error (MAE), and Mean absolute percentage error (MAPE)) in two case studies.