Hourly Forecasting of Solar Photovoltaic Power in Pakistan Using Recurrent Neural Networks

Table 5

Results of LSTM, Bi-LSTM, and SARIMA.

Weather	Model	RMSE	square	CV (RMSE) %
Sunny	LSTM (2 layers)	0.06	0.99	0.15
	Bi-LSTM	0.06	0.99	0.15
	SARIMA	1.43	0.26	4.57
Cloudy	LSTM (2 layers)	0.058	0.99	0.21
	Bi-LSTM	0.0025	0.99	0.0095
	SARIMA	1.76	0.40	7.03
Rainy	LSTM (2 layers)	0.157	0.91	0.60
	Bi-LSTM	0.12	0.95	0.54
	SARIMA	25.45	0.48	10.79
Partial cloudy	LSTM (2 layers)	0.18	0.81	0.51
	Bi-LSTM	0.06	0.99	0.17
	SARIMA	16.54	0.229	6.55
Dusty	LSTM (2 layers)	0.18	0.80	0.50
	Bi-LSTM	0.08	0.99	0.22
	SARIMA	2.53	0.274	7.75
Fog	LSTM (2 layers)	0.17	0.85	0.84
	Bi-LSTM	0.072	0.98	0.33
	SARIMA	3.81	0.19	25.4