[PDF][PDF] 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. … Results are compared with autoregressive integrated moving
average (ARIMA), backpropagation neural network (BPNN), and radial basis function neural …
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. … Results are compared with autoregressive integrated moving
average (ARIMA), backpropagation neural network (BPNN), and radial basis function neural …
Abstract
The modernization of the world has considerably reduced the prime sources of energy, such as coal, diesel and gas. Thus, alternative energy
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