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.

Critical aspects of wind energy systems in smart grid applications

“…This postures additional challenges to the precision and reaction time requirement for fault diagnostic and protection of such faults. In [24][25][26], modelbased approach was used to detect the abnormal physical parameters for DFIG. The major advantage of this approach was being independent from the signal signatures.…”

Design and Analysis of Different Types of Rotors for Pico-Turbine

“…However, density of air varies according to elevation, temperature and weather fronts. Density of air for 30˚C is 1.16 kg/m 3 [10].…”

Diagnosis & fault detection in wind energy conversion system

“…The NSP of the DC machine sends a reference of the electromagnetic torque to the NSP of the D.F.I.G by using their inputs and outputs and converters. A detailed presentation of the experimental benchmark is given in [13].…”