Abstract:
The ability of the power system distribution network to facilitate the additional
charging demand of plugin electric vehicles (PEVs) is critical to the successful
electrification of the transportation sector. Thus, the significance of a reliable
electricity system, particularly at the distribution network level, cannot be overstated.
An accurate assessment of the PEV charging load profile is critical for distribution
system reinforcement planning. In this paper a unique approach is adopted is
introduced to estimate aggregated PEV charging load based on the real-world
dynamics. The proposed methodology is based on the multivariate stochastic
modelling of PEV driving behavior, which is combined with powertrain simulations
performed on various models of PEVs operating under two different driving cycles to
determine main parameters i.e., energy consumption of PEV during the trip, initial
SOC at charging, and grid charging energy requirement factors to estimate daily PEV
charging demand based on real-world dynamics. Gird impact analysis is performed on
the local distribution network of National University of Sciences and Technology
(NUST), Islamabad, Pakistan, where the aggregated PEV charging load of levels 1,2
and 3 is integrated at respective nodes. The load flow analysis is performed to
determine the weakest nodes in the grid and the percentage of transformer loading due
additional PEV charging load. Furthermore, a technoeconomic grid reinforcement
solution is offered to reduce the detrimental influence of PEV charging load on grid
voltage stability.
