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An integration of ANN wind power estimation into UC considering the forecasting uncertainty

The development of wind generation has rapidly progressed over the last decade. With the advance in wind turbine technologies, wind energy has become competitive with other fuel-based generation resources. The fluctuation of wind, however, makes it difficult to optimize the use of wind power generation. Current practice ignores the possible available capacity of the wind generation during the unit commitment scheduling. This may cause operation issues and waste usable capacity when the installation of the wind generation increases. An accurate wind capacity forecasting is essential for efficient wind energy and capacity dispatching. To ensure the system reliability, one also has to consider the forecast uncertainty when integrating the wind capacity into generation planning. This paper discusses the development of an artificial neural network based wind forecast model with the consideration of wind generation uncertainty by using probabilistic concept of confidence interval. The data from a wind farm located in the Southern Oklahoma is used for this study