Nowadays natural resources are becoming more and more popular, mostly because of their economic advantages over other resources (oil, gas etc.) so their optimal usage gain more importance over time. One of these resources is wind energy which almost does the fewest harm to flora and fauna near power plants so people being able to get useful insights from data and therefore forcast the amount of producted energy can mean quite an opportunity to companies in the energy business to optimize their power plant’s utility and cost of maintenance.
In the light of these things, the goal of this thesis is to predict the production of wind farms with the help of data from other external farms which are relatively close and placed in the same area and enhancing the precision of the default forecasting solutions.
This knowledge discovery process can be followed in the document from data gathering and processing to creating and testing the performance of a forecasting model and evaluating the results we got.