COMPARATIVE ANALYSIS OF WIND POWER FORECASTING USING ARTIFICIAL NEURAL NETWORK (ANN) (International Journal of Engineering and Computer Science, 2017)
Forecasting is the establishment of future expectations by the analysis of past data, or the formation of opinions. Forecasting of the wind power generation may be considered at different time scales, depending on the intended application. Rapid growth of wind power generation in many countriesaround the world in recent years has highlighted the importance of wind power prediction however, wind power is a complex signal for modeling and forecasting.The wind sector in India has seen phenomenal growth during the past few years, catapulting India to fourth position in the world in terms of wind power installations.Despite the performed research work in the area more efficient wind power forecast methods are still demand. In this paper new strategy is proposed for this purpose. Forecast engine of the proposed strategy is an artificial neural network (ANN) owning artificial functions as the activation function of its hidden nodes. Moreover a new back propagation algorithm can be used. ANN is the best tool for forecasting the demand in electricity. The efficiency of the proposed prediction strategy is shown for forecastingof both wind power output of wind farms and aggregated wind generation of power system. Also perception rule, that rule help the wind power calculation such as total power, average, needed power, update and demand.