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Developing Decision Support Systems in public institutions such as the National Power Grid Companies require applying very efficient methods in order to support the decisions. The decision support system in the National Power Grid Companies can integrate the energy prediction achieved by some data mining algorithms that help managers to fundament their investment decisions in order to justify the financial feasibility. This is done by estimating all the benefits and costs during the life cycle. In order to estimate the revenues, we need to know with certain accuracy the output of these power plants. Due to the fact that the wind speed significantly fluctuates even during a day at the same location, the wind power output is difficult to be forecasted by statistical methods. In this paper we apply the data mining techniques on the available measured weather data in order to predict the wind power output and determine the financial feasibility of investment.