Long-term Forecasting of Intermittent Wind and Photovoltaic Resources by using Adaptive Neuro Fuzzy Inference System (ANFIS)

Forecasting of intermittent solar photovoltaic (PV) and wind resources is crucial for future power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy Inference System (ANFIS) approach for predicting wind and PV power outputs of the isolated Adrar's power system. The model formed by using real numerical weather measurements (wind speed, temperature, pressure, humidity, and solar irradiation), taken as input variables, and power outputs values as the output. Besides, metrics to calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE), have applied to denote forecast accuracy. The result verifies that ANFIS has a good perfection, and can be used as a reliable tool for modelling and prediction renewable energies.