The optimization initial value and micro-variation search algorithm and its simulation in parameter identification of doubly fed induction generator

Aiming at the problems of parameter identification of doubly fed induction generator (DFIG), which exists initial-value instability question and easy to get into the local optimization, a new identification method called optimization initial value and micro-variation search algorithm (OIVMSA) is proposed in this paper. Firstly, calculation the identification initial-value using input-output measurement data and constraint conditions determined by physical characteristics of DFIG, this initial-value is near by the object identification value. Secondly, hunting the global optimization from such initial-value by micro-variation step length, when the problem is defined using OIVMSA, it combines the advantage of rapidness and global optimization. Simulation results show that it is very effective. Such algorithm may be used to identify actual measurement parameter of DFIG, the concerned research work are done profoundly.