A tracking state estimator for nonsinusoidal periodic steady-state operation

This paper presents a tracking state estimator for systems operating under nonsinusoidal but periodic steady state conditions. Such operating states are being frequently observed in today's power systems due to the emerging nonlinear loads and power conditioning devices. Measurement equations are derived in discrete time and the sampling frequency is chosen according to the highest harmonic of interest. The proposed estimator is designed to be computationally efficient by transforming the measurement equations in a special manner so that the sparsity of the corresponding discrete time matrix equations is significantly enhanced. Zero injection constraints are also included to take advantage of the increased redundacy. The paper presents results of simulations under both normal measurement noise as well sis with gross errors existing in the measurements. Performance of the developed algorithm is evaluated both in terms of cpu time and accuracy based on the simulations.