V2G Optimization for Dispatchable Residential Load Operation and Minimal Utility Cost

Abstract

Electric Vehicles (EVs) are gaining popularity among consumers and are expected to play a significant role in the future of transportation. Within this paper, a reverse auction is formulated through an optimization problem to minimize the utility energy cost using Vehicle-to-Grid (V2G) operation, as well as transition residential communities to dispatchable aggregate constant load profiles for demand response (DR). The evolution-ary V2G Auction (eV2GA), including the non-dominated sorting genetic algorithm (NSGA-II), is proposed for the formulated problem. It uses co-simulation with OpenDSS for power flow analysis as part of the objective function to account for physical constraints of infrastructure on the cost analysis. The results are verified against a greedy method in two case studies on the IEEE 123 test feeder with modified residential load showing over 20 % reduction in cost from no v2G. It is demonstrated that physical power system constraints, such as line active power flow limits, may be implemented into the optimization through the proposed approach and do affect the V2G design solution by placing influence on location of the selected EV s in the distribution system.