From an economic perspective, minimizing the grid impacts of large-scale plug-in electric vehicle (PEV) charging tends to result in coordination strategies that seek to fill the overnight valley in electricity demand. However such strategies can result in high
charging power, raising the possibility of local overloads within the distribution grid and of accelerated battery degradation. The talk will establish a framework for PEV charging coordination that facilitates the tradeoff between the total generation cost and the
local costs associated with overloading and battery degradation. A decentralized approach to solving the resulting large-scale optimization problem involves each PEV minimizing their charging cost with respect to a forecast price profile while taking into account local grid and battery effects. A central manager collects the proposed charging strategies from the participating PEVs, updates the price profile based on this latest PEV information, and broadcasts the revised price profile. The process then repeats. It will be shown that this iterative process converges, under mild conditions, to the unique, efficient (socially optimal) solution.