The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS)

and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application

the pattern of the last short WPTS is recognized

then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations. This work is jointly supported by National Basic Research Program of China (973 Program) (No. 2013CB228204)

Australian Research Council Project (No. DP120101345)

NSFC-EPSRC Collaborative Project (No. NSFC-513111025-2013

No. EPSRC-EP/L001063/1) and State Grid Corporation of China.