Intelligent systems for predicting and analyzing data in Power Grid Companies

Abstract

Developing intelligent systems in public institutions such as the Power Grid Companies require efficient methods in order to support better decisions. The Power Grid Companies must fundament their investment decisions by estimating all the benefits and costs during the life cycle of a wind power plant. In order to estimate the financial feasibility, they need to know with certain accuracy the output of these power plants. But the main problem is that the wind power output is difficult to be forecasted by statistical methods due to the fact that the wind speed significantly fluctuates even during a day at the same location. Also, the reserves must be properly dimensioned in order to prevent system's crash. In this paper we present a solution for developing an intelligent system in the National Power Grid Company that can predict the wind power output and allocate the resources in order to improve the financial feasibility of investment.