A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies.

Erdogan, Nuh; Kucuksari, Sadik; Murphy, Jimmy

Abstract

This study proposes a multi-objective optimization model to determine the optimal charging infrastructure for a transition to plug-in electric vehicles (PEVs) at workplaces. The developed model considers all cost aspects of a workplace charging station, i.e. daily levelized electric vehicle supply equipment (EVSE) infrastructure cost, PEV energy and demand charges. These single-objective functions are aggregated in a multi-objective optimization framework to find the Pareto optimal solutions. Smart charging strategies with interrupted and uninterrupted power profiles are proposed to maximize the use of EVSE units. The charging behavior model is developed based on collected workplace charging data. The model is tested with various scheduling policies to investigate their impact on the behaviors of EVSE types from different perspectives. Finally, a sensitivity analysis is performed to assess the impacts of battery sizes and onboard charger ratings on cost behavior. It is shown that the proposed model can achieve up to 7.8% and 14.6% cost savings as compared to single-objective optimal models and the current charging practice, respectively. The unit cost is found to be more sensitive to scheduling policies than the charging strategies. It is also found that the flexibility ratio policy gives the best PEV scheduling with the lowest unit cost and the most efficient use of the grid assets.

Citation

ERDOGAN, N., KUCUKSARI, S. and MURPHY, J. 2022. A multi-objective optimization model for EVSE deployment at workplaces with smart charging strategies and scheduling policies. Energy [online], 254(Part A), article number 124161. Available from: https://doi.org/10.1016/j.energy.2022.124161

• Journal Article Type: Article
• Acceptance Date: Apr 28, 2022
• Online Publication Date: May 14, 2022
• Publication Date: Sep 1, 2022
• Deposit Date: May 16, 2022
• Publicly Available Date: May 16, 2022
• Journal: Energy
• Print ISSN: 0360-5442
• Electronic ISSN: 1873-6785
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 254
• Issue: Part A
• Article Number: 124161
• DOI: https://doi.org/10.1016/j.energy.2022.124161
• Keywords: Electric vehicles; Plug-in electric vehicles; Vehicle charging points; Vehicle charging infrastructure; Multicriteria decision making; Multicriteria optimisation; DCFC; Demand charge; EVSE; Multi-objective optimization; Plug-in electric vehicles; Workplac
• Public URL: https://rgu-repository.worktribe.com/output/1669361