On-line parameter identification for excitation system based on PMU data

Abstract

Parameter identification of excitation systems is of great importance for power system analysis, operation and control. In this paper, on-line parameter identification with PMU data is formulated as an optimization problem, which minimizes the exciter voltage error during a certain time. The errors are the differences between measured exciter voltage (field data) and simulated exciter voltage using identified parameters. The optimization problem is nonlinearity as it involves integrator and then solved by genetic algorithm (GA). Furthermore, to ensure the creditability of the solutions obtained with GA, the ordinal GA, which is a modification of GA with the philosophy of ordinal optimization, is applied. Case studies in Anhui power grid show the effectiveness of the proposed approach.