Portal de Periódicos da CAPES

Current status of wind energy forecasting and a hybrid method for hourly predictions

2016; Elsevier BV; Volume: 123; Linguagem: Inglês

10.1016/j.enconman.2016.06.053

1879-2227

İnci Okumuş, Ali Dinler,

Wind Energy Research and Development

Generating accurate wind energy and/or power forecasts is crucially important for energy trading and planning. The present study initially gives an extensive review of recent advances in statistical wind forecasting. Numerous prediction methods for varying prediction horizons from a few seconds to several months are listed. Then in the light of accurate results in the literature, the present study combines the adaptive neuro-fuzzy inference system (ANFIS) and an artificial neural network (ANN) for 1 h ahead wind speed forecasts. The performance results show the mean absolute percentage errors (MAPE) of 2.2598%, 3.3530% and 3.8589% at three different locations for daily average wind speeds.