Electrical and Computer Engineering Publications

Document Type

Conference Proceeding

Publication Date



IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

URL with Digital Object Identifier



In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging periods. On the other hand, the approach reduces the pressure on the grid by balancing the grid load. Two methods, the greedy algorithm and nonlinear programming, are considered along with users’ charging preferences and durations. For scheduling small numbers of charging activities, the nonlinear programming model achieves better load balancing than the greedy algorithm; however, for scheduling medium to large numbers of charging activities, the greedy algorithm has a clear advantage in terms of time complexity.