Harmonic Source Estimation in Distribution Systems

In power systems, knowledge of system state is required to operate management and control issues, such as energy dispatching and protection coordination. The authors have recently proposed a novel procedure for harmonic source estimation, based on a Bayesian approach, which is aimed at giving distribution network operator information about the possible presence of harmonic producing loads, along with an indication about the reliability of such information. Both measured (the real-time information coming from the field) and a priori information, along with their uncertainty, are used to estimate the forcing terms (i.e., the harmonic currents actually injected by the nonlinear loads) and to evaluate the uncertainty of these estimates. In this paper, significant improvements in the procedure are presented. A Metropolis-Hastings approach is applied to obtain the posterior distributions of each Bayesian estimation process. As a consequence, the harmonic sources are evaluated, along with a full uncertainty description. The methodology is applied to a small distribution network, and the obtained results are properly analyzed