The randomness and fluctuation of wind power bring challenges to the integration of wind power to the power grid. The error range estimation of predicted power for wind farms can provide important information for the operation and the scheduling of power system with wind power. So

an interval rolling estimation method for daily wind power forecast errors is proposed

which is based on hidden Markov model. The hidden Markov model can be built to achieve fast estimation of wind power error fluctuation range under the certain confidence level

and the local weighted regression smoothing method is used to deal with the error interval. Based on the actual data

the simulation results show that this method can give the fluctuation range of the wind power prediction error and provide more comprehensive information for the power system scheduling and control

the allocation of backup capacity

the risk assessment and so on.