DECOUPLING EVALUATION METHOD FOR WIND POWER PREDICTION ERROR BASED ON K-NEAREST NEIGHBOR SEARCH

A decoupling evaluation method for a wind power prediction error based on k-nearest neighbor search first calculates a prediction error caused by a power correction stage based on information of planned and actual available capacities, finds real meteorological data closest to numerical weather prediction (NWP) data from historical operation data based on a k-order nearest neighbor principle, estimates, through average approximation of a k-order nearest neighbor, a prediction error caused by a modeling stage, and finally calculates a prediction error caused by an NWP stage based on a total prediction error. The method does not need to directly obtain a predicted wind power conversion model of a wind farm, but performs highly-reliable quantitative evaluation on errors of different stages in a wind power prediction process to further obtain an error contribution rate of each stage, thereby accurately locating a weak stage of a wind power prediction algorithm.