Dynamic parameter identification of asynchronous motor based on algebraic analysis and optimization modelling
                                                 FENG Li1, LI Shangyuan2, CHEN Tao1, WU Yingxia1, WANG Zhen2
(1.State Grid Chongqing Electric Power Company, Chongqing 400014, China;2.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract: Aiming at identification of key asynchronous motor load (AML) parameters for online application, the datamodel hybrid modelling framework was firstly given and a datamodel hybrid analytic method of AML dynamic parameter identification was developed. With the active/reactive power, terminal voltage and current measured by PMU as input, the fundamental four parameters, including the rotor inertia, rotor transient reactance, rotor steady reactance, rotor time constant were derived by algebra analysis based on the AML dynamic equations. Another class of datadriven and statespace model based optimization modelling method was introduced, in which a genetic algorithm (GA) was adopted to seek the minimum fitting error between the modelled active/reactive power and the PMU counterparts. Finally, a comparison study between these two methods was conducted on a modified threemachine ninebus systemthe. The results indicate that the proposed algebra analytic method can outperform the optimization method in both identification accuracy and computation efficiency.

Key words: asynchronous motor; dynamic parameter identification; algebraic analytic analysis; optimization modelling