Abstract
This paper introduces modeling of the probabilistic dependence between different structures of power system devices, employing the “Copulas” analytical tool for correlating among multivariate outcomes. Copulas have become a popular analytical tool in multivariate modeling, where recently has been applied in many fields. Here, the basic properties and theorems of Copulas along with their contributions to Monte Carlo method are described. A case study has been performed on a distribution substation in Tehran, in which enormous information was gathered using an installed data logger. Then, investigation is carried out based on the measured data. The recorded data paves the way for pursuing further analysis that is associated with simulating statistical correlation between uncharacteristic harmonics and realistic unbalanced conditions for a voltage-source inverter at the point of common coupling (PCC).
