Abstract
Battery electric vehicles can help reduce fossil fuel consumption and greenhouse gas emissions. Specifically, workplace charging can alleviate the curtailment of renewable resources, while providing charging opportunities to long-range commuters. In this work, a comprehensive smart-charging protocol for workplace charging is proposed. The protocol first uses an ordering strategy, based on each vehicle’s load shifting flexibility, to develop a queue. Next, a decentralized smart-charging strategy is used that allows battery electric vehicles to generate their own charging profile via linear programming. By using an appropriate cost signal, the proposed smart-charging strategy can generate a parking structure demand load with desirable characteristics. Finally, an assignment algorithm is proposed to assign battery electric vehicles to octopus chargers. Driving patterns from the National Household Travel Survey are used to simulate workplace charging for parking structures under various charging scenarios. The proposed ordering strategy resulted in improved peak reductions for all simulated charging scenarios, when compared with chronological ordering. Furthermore, monthly electricity costs and the number of required chargers were both reduced in all cases where smart charging was combined with the proposed ordering strategy, compared to uncontrolled charging. Thus, the proposed protocol can reduce electricity and charging infrastructure costs associated with workplace charging.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.