A Congestion Forecast Framework for Distribution Systems with High Penetration of PV and PEVs

This paper presents a congestion forecast framework for electrical distribution systems with high penetration of solar photovoltaic and plug-in electric vehicles. The framework is based on probabilistic power flow to account for the uncertainties in photovoltaic production and load demand. The proposed framework has been implemented and tested using the data of the real distribution grid of Chalmers University of Technology campus. Cases studies have been carried out using the framework to analyse the impact of different local production levels and operating modes of solar photovoltaic inverter. The results have shown that cumulative probability for network congestion in branches and transformers would increase by 30% and 20% respectively, when the level of local PV generation, demand and PEVs demand to increase by 100%, 95% and 100% respectively. Also, results have shown that network congestion in branches and transformers is 4% and 8% respectively, more likely to occur in the constant-V mode as compared to constant-pf mode. These results can help distribution system operators to predict any upcoming congestion in their system and subsequently help them in taking suitable actions in order to mitigate congestion.