Time domain modeling and identification of nonlinear loads using discrete time-filtering estimator

Non-linear loads result in harmonic voltage and current waveforms. This prompted the need for accurate harmonic impedance or admittance measurement technique. This work presents a fast and efficient on line identification of non-linear loads in power systems. The proposed technique is an application of a discrete time-dynamic filter based on stochastic estimation theory, which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signals. The non-linear load admittance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition of the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional least square method.