Aggregative Game for Distributed Charging Strategy of PEVs in a Smart Charging Station

This paper proposes a charging strategy for plug-in electric vehicles (PEVs) in smart station (SCS) that considers load constraints and time anxieties. Due to the rapidly growing demand of PEVs capacity investments infrastructure, PEV needs be subject overload limits, beyond which failures can occur. The anxiety is presented address some uncertainties may arise while PEVs. Under an aggregative game framework, this constructs price-driven model minimize costs by choosing optimal strategy. Meanwhile, since driver information aggregated item cost function, drivers’ privacy protected. Then, distributed reflected forward–backward (RFB) splitting method developed search generalized Nash equilibria (GNE) game. convergence proposed algorithm effectiveness are verified detailed simulation results.