基于粒子群优化算法的变压器参数辨识

Parameter Identification of Transformer Based on Particle Swarm Optimization Algorithm

基于模型的变压器保护原理需要对变压器绕组参数进行精确辨识.利用双绕组变压器的参数辨识方程,使用粒子群优化算法,提出了新的参数辨识算法.消除了最小二乘法计算速度慢、计算量大的局限性,可以实现对变压器绕组参数的在线精确辨识.通过Matlab/Simulink对算法进行仿真,结果表明,该算法能够正确辨识变压器绕组电阻和漏感参数,具有较好的应用前景.

New transformer protection principles based on models calls for accurately identifying transformer winding parameters. Parameter identification equations of single-phase double-winding transformer and three-phase three-winding transformer are deduced. And then a new parameter identification algorithm is put forward on the basis of particle swarm optimization algorithm. The new algorithm eliminates the limitation of least squares method and can realize precise identification of parameters of transformer winding. The simulation of Matlab/Simulink shows that the algorithm can correctly identify leakage inductance and winding resistance parameters of transformer. This algorithm has a good application prospect.