Abstract:

Several studies have presented electric vehicle smart charging schemes to increase the temporal matching between photovoltaic generation and electric vehicle charging, including one that aims to reduce net-load variance. This method has proved, through simulations that the self-consumption could be increased, but the benefit of the approach has not been tested on a low voltage distribution system. To increase the quality of grid impact analyses of the smart charging scheme, probabilistic methods that include input and spatial allocation uncertainties are more appropriate. In this study, a probabilistic load flow analysis is performed by modelling the variability of electric vehicle mobility, household load, photovoltaic system generation, and the adoption of photovoltaic system and electric vehicle in society. The smart charging technique improves the low voltage distribution system's performance and raises the correlations between network nodes, according to the findings. It's also been demonstrated that concentrated allocation has more severe consequences, especially at lower penetration levels. This work can be used to construct a probabilistic impact analysis of smart charging, which will enable society to integrate more electric vehicles and photovoltaic systems for a more sustainable future.