An intelligent energy management system for large-scale charging of electric vehicles

Abstract

The problem of large-scale charging of electric vehicles (EVs) with consumer-imposed charging deadlines is considered. An architecture for the intelligent energy management system (iEMS) is introduced. The iEMS consists of an admission control and pricing module, a scheduling module that determines the charging sequence, and a power dispatch module that draws power from a mix of storage, local renewable energy sources, and purchased power from the grid. A threshold admission and greedy scheduling (TAGS) policy is proposed to maximize operation profit. The performance of TAGS is analyzed and evaluated based on average and worst-case performance measures and the optimality of TAGS is established for some instances. Numerical simulations demonstrate that TAGS achieves noticeable performance gains over benchmark techniques.