Chaotic characteristics identification and trend prediction of running state for wind turbine

The nonlinear dynamic model is built for the chronological state parameter series of wind power generator set,the dynamic characteristics of its running state are analyzed and its chaotic characteristics are verified,based on which its chaotic prediction method is studied according to the phase space reconstruction theory.The proposed weighted first-order local prediction method is tested with the actual operational data of a wind power generator set and the results show that,the chaotic prediction method is feasible with higher precision.