Methodology for the Creation of More Realistic Scenarios of Rooftop PVs Allocation in Monte Carlo Studies

Due to the increased installation of rooftop PV generators in electric power distribution systems and the intrinsic uncertainties, impact studies require probabilistic methods such as Monte Carlo simulation. An important uncertainty of the Monte Carlo simulation involving rooftop PV systems is the local of installation. Considering all the customer units from the utility database with equal probability for receiving a rooftop PV generator provides unrealistic results. For instance, customers of a building should not receive the same treatment as houses. In this context, to allow more realistic studies, this work presents a methodology for selecting the most probable customer units to install rooftop PV generators considering net metering tariff. The methodology consists of reading a real complete database of a distribution utility, sizing the rooftop PV generators, filtering the customer units with the highest potential to receive a PV generator, and creating the scenarios for the Monte Carlo study. At the end, computational simulations using OpenDSS are carried out in two real distribution networks to illustrate the application of the method.