Probabilistic Modeling and Analysis of Aggregated Electric Vehicle Charging Station Load on Distribution System

Plug in electrical vehicles (PEVs), due to their high efficiency and low carbon emissions are considered as an effective alternative against depleting sources of fossil fuel and environmental concerns. Owing to growing preference of PEVs as a sustainable mode of transport, charging stations are expected to increase in residential area in future. However, PEVs will add significant additional load to the existing distribution system. The overall charging demand of PEVs tends to be uncertain as it depends on various uncertain factors such as battery capacity, charging duration etc. In this work, firstly overall charging demand at charging station is probabilistically modeled using queuing theory. Further probabilistic load flow (PLF) analysis is employed to analyze the impact of increased load due to charging station. The analysis is carried out by applying point estimate method (PEM) for probabilistic load flow and system operational parameters like voltage profile and losses are investigated on IEEE-69 bus radial distribution system. The results of PEM are also compared with Monte Carlo simulation (MCS) method.