An EV Charging Scheduling Mechanism to Maximize User Convenience and Cost Efficiency

TL;DR

This paper presents an online EV charging scheduling algorithm for microgrids that optimizes cost and user convenience, utilizing load forecasting to achieve near-optimal solutions and outperform previous methods.

Contribution

The paper introduces a bi-objective optimization framework and a close-to-optimal online scheduling algorithm that balances cost and user convenience in EV charging.

Findings

Achieves optimal charging cost in simulations.

Provides near-optimal user convenience.

Improves load forecasting accuracy.

Abstract

This paper studies charging scheduling problem of electric vehicles (EVs) in the scale of a microgrid (e.g., a university or town) where a set of charging stations are controlled by a central aggregator. A bi-objective optimization problem is formulated to jointly optimize total charging cost and user convenience. Then, a close-to-optimal online scheduling algorithm is proposed as solution. The algorithm achieves optimal charging cost and is near optimal in terms of user convenience. Moreover, the proposed method applies an efficient load forecasting technique to obtain future load information. The algorithm is assessed through simulation and compared to the previous studies. The results reveal that our method not only improves previous alternative methods in terms of Pareto-optimal solution of the bi-objective optimization problem, but also provides a close approximation for the load forecasting.