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Data reconciliation and gross error detection applied to wind power

Abstract The current paper presents a method to identify and estimate gross errors for linear dynamic systems using polynomial approximation. The method presented in a previous paper which uses linear dynamic reconciliation, is extended to allow the dynamic estimation of errors. This method is applied to the doubly fed induction generator (DFIG) of a wind turbine. The technique is validated on an experimental system used to emulate the working of the wind turbine.