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Nowadays, there has been a rapid growth in global usage of the electronicvehicles (EV). Despite apparent environmental and economic advantages of EVs,their high demand charging jobs pose an immense challenge to the existingelectricity grid infrastructure. In microgrids, as the small-scale version oftraditional power grid, however, the EV charging scheduling is morechallenging. This is because, the microgrid owner, as a large electricitycustomer, is interested in shaving its global peak demand, i.e., the aggregateddemand over multiple parking stations, to reduce total electricity cost. Whilethe EV charging scheduling problem in single station scenario has been studiedextensively in the previous research, the microgrid-level problem with multiplestations subject to a global peak constraint is not tackled. This paper aims topropose a near-optimal EV charging scheduling mechanism in a microgrid governedby a single utility provider with multiple charging stations. The goal is tomaximize the total revenue while respecting both local and global peakconstraints. The underlying problem, however, is a NP-hard mixed integer linearproblem which is difficult to tackle and calls for approximation algorithmdesign. We design a primaldual scheduling algorithm which runs in polynomialtime and achieves bounded approximation ratio. Moreover, the proposed globalscheduling algorithm applies a valley-filling strategy to further reduce theglobal peak. Simulation results show that the performance of the proposedalgorithm is 98% of the optimum, which is much better than the theoreticalbound obtained by our approximation analysis. Our algorithm reduces the peakdemand obtained by the existing alternative algorithm by 16% and simultaneouslyachieves better resource utilization.

Microgrid Revenue Maximization by Charging Scheduling of EVs in Multiple Parking Stations