Electric Vehicle Scheduling Considering Co-Optimized Customer and System Objectives
Efficient electric vehicle (EV) scheduling is a multi-objective optimization problem with conflicting customer and system operator interests, especially during vehicle-to-grid implementations. Economic charging while minimizing battery degradation and maintaining system load profiles couple the interests of these two entities. This paper focuses on identifying the relationships between these objectives and proposes to use an augmented epsilon-constrain (AUGMECON) based technique to implement two-way and three-way multi-objective optimizations. The importance of using these objectives in peak-shaving and valley-filling for an aggregated (residential) EV fleet is discussed. The proposed solution provides a look-ahead strategy into effective EV scheduling by co-optimizing multiple objectives. To provide operational guidance to utilities and customers, an optimal solution may be selected from those represented by the Pareto fronts.
F. Maigha and M. Crow, "Electric Vehicle Scheduling Considering Co-Optimized Customer and System Objectives," IEEE Transactions on Sustainable Energy, vol. 9, no. 1, pp. 410-419, Institute of Electrical and Electronics Engineers (IEEE), Jan 2018.
The definitive version is available at https://doi.org/10.1109/TSTE.2017.2737146
Electrical and Computer Engineering
Keywords and Phrases
Charging (batteries); Degradation; Electric load management; Electric vehicles; Multiobjective optimization; Optimization; Sales; Scheduling; Solar cells; AUGMECON; Battery degradation; Load modeling; Multi-objective optimization problem; Multiple-objectives; Operational guidance; State of charge; Vehicle scheduling; Vehicle-to-grid; Multi-objective optimization; V2G
International Standard Serial Number (ISSN)
Article - Journal
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jan 2018