Optimal electric vehicle charging with dynamic pricing, customer preferences and power peak reduction
ABSTRACT: We consider a provider of electric vehicle charging stations that operates a network of charging stations and use time varying pricing to maximize profit and reduce the impact on the electric grid. We propose a bilevel model with a single leader and multiple disjoint followers. The customers (followers) make decisions independently from each other. The provider (leader) sets the price of charging for each station at each time slot, and ensures there is enough energy to charge. The charging choice of each customer is represented by a combination of a preference list of (station, time) pairs and a reserve price. The proposed model thus accounts for the heterogeneity of customers with respect to price sensitivity and charging preferences. We define a single-level reformulation based on a reformulation approach from the literature on product line optimization, and we report computational results that highlight the efficiency of the new reformulation and the potential impact of our approach for reducing peaks on the electricity grid.
Authors
- Miguel F. Anjos (ORCID: https://orcid.org/0000-0002-8258-9116)
- G. Guillot (ORCID: https://orcid.org/0000-0003-0675-8325)
- Luce Brotcorne (ORCID: https://orcid.org/0000-0002-0906-7709)
Institutions
- Institut national de recherche en sciences et technologies du numérique (FR)
- Maxwell Institute for Mathematical Sciences (GB)
- University of Edinburgh (GB)
Publication Details
- Journal
- INFOR Information Systems and Operational Research
- Published
- 2025-02-15
- DOI
- https://doi.org/10.1080/03155986.2025.2463189
- Citations
- 2
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 1.46
Funders
- National Science Foundation