The invention belongs to the field of electric system forecasting, and provides a method for estimating a wind power forecasting error burst based on a hidden markov model. A wind power ultrashort term forecasted value reported to a dispatching department for a wind power plant is a deterministic point forecasting and given in a curved mode, but the problem that the forecasting accuracy is not high exists. By introducing an HMM model, modeling is performed on the wind power ultrashort term forecasting error, the error burst is processed by means of a locally weighted regression scatter plot smoothing method, the result accuracy is improved and the result conservation is lowered. The wind power forecasting error burst can be obtained, an error fluctuation state transition matrix can be obtained, and references are provided for dispatching operation.