Abstract
This paper develops a new approach for producing probabilistic wind power forecasts using a single forecast. The Singular Spectrum Analysis technique is used as the forecasting technique. Given the confidence interval calculated for the single forecast, a large number of random forecasts were generated through the Monte Carlo method. The purpose of generating probabilistic wind power forecasts is to use the results in a stochastic programming unit commitment problem. Therefore, probabilistic forecasts are reduced to a small number of representative forecast scenarios by applying a scenario reduction algorithm. The stability of the scenario reduction algorithm is also evaluated. The results indicate that the insignificant changes of operational cost of the stochastic programming problem reflect a deletion of unimportant forecast scenarios
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