wind power forecasting

In recent years, increasing use of intermittent generations, such as wind power, affects power system operation and security and electricity market economics. The improvement of the performance of wind power forecast tools have significant technological and economic impacts on the system operation with increased wind power penetration. In this paper, a new Hybrid Iterative Forecast Method (HIFM) for wind power forecasting is presented. Wind power forecast strongly depends on wind speed prediction and wind speed is much correlated with temperature. An important contribution of this paper is modeling the interactions of different weather conditions and wind speed signals. Moreover, a two stage feature selection technique is also introduced for selecting the most relevant and the less redundant input variables. The forecast accuracy of the proposed wind power prediction strategy is evaluated by means of real data of wind power farms of Iran's and Spain's power systems.