Probabilistic Risk Assessment of an Active Distribution Network Using Monte Carlo Simulation Approach

With rapid advancements in distribution networks, renewable distributed generation (DG) sources, such as wind and photovoltaic generators (PVGs), have gradually become prominent. The addition of such DGs, increases the amount of uncertainty in an already dynamic system with uncertain loads. Risk is inherently associated with uncertainty. To account for uncertainties, probabilistic approaches can provide a significant contribution. This paper deals with the evaluation of probabilistic line overload risk assessment of an active distribution network, considering load and DG uncertainties. The modified IEEE 13-bus test system was used to evaluate line overload risk indices (LORIs) using the numerical Monte Carlo (MC) simulation approach. The conventional (N-1) security criterion was used for assessing risk indices. The lines were quantified, based on computed risk indices; and, consequently, system risk was computed. DIgSILENT PowerFactory software was used to conduct the required simulations.