Fairness-Aware Optimization of Vehicle-to-Vehicle Interaction for Smart EV Charging Coordination (2304.02232v1)

Abstract: As the number of electric vehicles (EVs) continues to grow, there is an increasing need for smart charging strategies. This paper exploits the vehicle-to-vehicle (V2V) concept to leverage EVs' diverse charging patterns and unlock the value of flexibility by enabling energy transfer among EVs. We formulate a cost minimization problem for an EV charging station to optimize the V2V schedule together with vehicle-to-grid (V2G), grid-to-vehicle (G2V) charging, as well as the use of renewable energy. When EVs perform V2V to transfer energy to charge EVs, the traditional cost-minimizing approach may overuse some EVs with lower costs to perform V2V. We address the fairness issue by developing fair V2V energy transfer strategies to avoid the excess discharge from individual EVs. We introduced three kinds of fairness metrics in the V2V optimization problem to demonstrate the fair energy transfers. In addition, we formulate baseline optimization problems without V2G or V2V and compare the results to prove the potency of V2V concept along with V2G method. The simulation results demonstrate that V2V can significantly reduce EV charging costs and highlight the trade-off between fairness enforcement and charging cost minimization.