Vehicle to grid from the Electric Vehicle point-of-view to reduce peak demand and system cost

Abstract

The study presents Electric Vehicle (EV) Point-of-View (POV) Vehicle to Grid (V2G) optimisation, where the system knows the trips and energy demand of the EV. This allows it to be less conservative in the departure State of Charge (SoC) of the EV battery. The peak and cost reduction of Vehicle POV optimisation are compared with state-of-the-art Location Point-of-View optimisation, this is, the car can do V2G but it has to depart each location with at least 80% SoC as the next trip energy demand is unknown. A Mix Integer Linear Programming (MILP) V2G optimisation approach is presented to reduce peak demand and total system cost of a fleet of EVs travelling between several residential locations and one common workplace. Simulations were conducted with 26 EVs unevenly distributed between five residential locations and commuters to a common workplace. The results indicate little differences in the reduction of peak demand between both POVs of V2G optimisation. However, the system cost can be further reduced with Vehicle Point-of-View optimization, saving an additional 200 euros annually per household by transporting cheaper energy from workplaces to residential locations.