Optimization of grid connected bidirectional V2G charger based on multi-objective algorithm

This paper presents a novel multi-objective approach to grid connected plug-in hybrid electric vehicle (PHEV) that uses for peak load levelling and load variance minimization. Meanwhile, this optimization technique sizes the capacitor of DC-link to provide sufficient reactive power compensation. This optimization technique is based on fuzzy-decision-making predictive control (FDMPPC) strategy which can be able to provide of peak load levelling and capacitor sizing of battery charger of PHEV, simultaneously. The proposed method is applied to the IEEE 123 test feeder, using time series analysis over a diurnal, 24-hour, simulation period. The optimization results show that the power load curve is effectively driven to follow the target loading and the grid voltage is successfully regulated.