Synchronous Machine Parameter Estimation Using Orthogonal Series Expansion

Abstract This paper presents an alternative to estimate armature circuit parameters of large utility generators using real time operating data. The alternatives consider the use of orthogonal series expansions in general and Hartley series in particular. The main idea considers the use of orthogonal series expansions for fitting operating data (voltage and currents measurements) and/or synthetic input-output data. This allows writing a set of linear algebraic equations that can be solved for the unknown parameters using the pseudoinverse. Hence, the essence of the approach is the linear state estimation and the purpose of generalizing the solution to accept orthogonal series expansion in general is indeed providing ‘windows’ to view the same problem. Although solutions are the same in all domains one wishes to employ the window that gives the best view and the most efficient computation. The approach may be used for static as well as dynamic problems. The approach is tested for noise corruption likely to be found in measurements. The method is found to be suitable for the processing of digital fault recorder data to identify synchronous machine parameters.