Yang Minggui1£¬Yang Xinning1£¬Liu Jianfeng2£¬Xu Qingfa1£¬Wei Wei1
(1.School of Electrical Engineering,Xi'an Jiaotong University,Xi'an 710049,¡¡China;2.School of Sciences,Xidan University,Xi'an 710053,China)
Abstract:A method is presented to identify synchronous machine rotor parameters with four steps.Good initial values in parameter identification are necessary for the traditional output error method £¨OEM£© algorithm£¬ so first the genetic algorithms £¨GA£© global searching ability is utilized to find parameters closed to the optimum values; the synchronous machine parameters can be identified accurately with the aid of these parameters; then the BP neural network is exerted a perfect training; and finally a well trained neural network is employed to identify machine parameters under the specific operating conditions.In this way the GA global searching,the OEM local searching ability and the real time capability of BP neural network can fully play their roles.A simulation test for 111 kVA£¬440 V synchronous machine confirms the validity of this method. It takes only 0.008 s to complete a parameter identification with enough accuracy£®
Keywords:synchronous machine;parameter identification;artificial neural network;genetic algorithm;output error method