基于线对线突然短路的同步电机瞬态参数辨识

准确地辨识同步电机参数,是分析电力系统运行和控制系统设计的前提.利用最小二乘或卡尔曼滤波等方法辨识电机三相同时突然短路试验数据,是传统电机参数辨识的主要方式.受同步电机三相同时突然短路的可操作性和电机参数模型的强非线性等因素的影响,电机瞬态参数难以准确测量.利用改进的小波变换和人工神经元网络辨识参数的新方法,结合容易实现的同步电机线对线突然短路试验,辨识得到了三相同步电机的瞬态参数,有效提高了电机参数的辨识精度.仿真试验表明,该方法是有效的.

Parameters identification of synchronous electric machine based on line-to-line sudden short circuit

An accurate identification of the electromagnetic parameters of synchronous electric machine is the precondition for analyzing power system running and controlling system design. It is a traditional way to identify the parameters of sudden three-phase short circuit with least-square and Kalman filtering. Influenced by the maneuverability of the synchronous machine sudden three-phase short circuit and the nonlinear of the machine parameter model, the machine parameters are difficult to measure. By combining the new method of improved wave transform and artificial neuron network with the synchronous machine sudden line-to-line short circuit test in identifying the parameters, the transient parameters of three phase synchronous machine were identified. The identifying precision of the parameters was improved. The simulation test proves that the method is effective.