电力系统暂态仿真的模型参数不准确导致了仿真结果和实际量测的差异,限制了其在线应用,而基于动态过程量测的参数在线辨识方法是解决问题的一个途径。在线参数辨识的信息量限制了参数辨识的精度,需要筛选出对电力系统动态过程影响较大的主导动态参数进行辨识。提出了基于Volterra级数的主导动态参数筛选方法,并与传统的灵敏度方法进行比较。研究结果表明,基于Volterra级数的主导动态参数选择方法避免了扰动方式的影响,更适合于主导动态参数的选择。
During power system transient simulation the imprecision of model parameters leads to the discrepancy between simulation results and measured results, so that the reliability of on-line transient simulation is restricted. The on-line identification of parameters obtained by dynamic measurement of transient process would be an approach to solve this problem, however, the abundant amount of information affects the accuracy of on-line identification, for this reason it is necessary for the identification to screen out dominant parameters which primarily influence power system dynamic process. The authors propose a Volterra series based method to screen out dominant parameters and compare the proposed method with traditional sensitivity method. Research results show that the dominant parameter selection method based on Volterra series can avoid the influence of fault types, so it is more suitable for the selection of dominant parameters.