Study on modeling of wind generator based on data reduction preprocessing

The technology of modeling and simulation is basic and necessary for researches on design, operation, protection and control of wind power generators. This paper establishes wind turbine model of doubly-fed induction generator (DFIG) on the DIgSILENT platform. In order to improve modeling precision, a cluster of actual operation data, sampled from a wind farm in Guangdong province, are used. Furthermore, a preprocessing module for data deviation reduction is deigned, which considers the compensation factor used for operation efficiency. Then, the model parameters could be identified via parameter identification module of DIgSILENT software. Test examples by actual operation data show that, modeling in such a way can meet the simulation requirement of relevant kind of wind generators.