2015/02/05 by I. Safak Bayram, Bayram, Islam Safak, Ali Tajer +5
Engineering · #Advanced Battery Technologies Research #Electric Vehicles and Infrastructure #FOS: Mathematics #Optimization and Control (math.OC) #Transportation and Mobility Innovations
paper · pdf · doi:10.48550/arxiv.1502.01524
openalex publication_date 2015/02/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In order to foster electric vehicle (EV) adoption, there is a strong need for\ndesigning and developing charging stations that can accommodate different\ncustomer classes, distinguished by their charging preferences, needs, and\ntechnologies. By growing such charging station networks, the power grid becomes\nmore congested and, therefore, controlling of charging demands should be\ncarefully aligned with the available resources. This paper focuses on an EV\ncharging network equipped with different charging technologies and proposes two\nframeworks. In the first framework, appropriate for large networks, the EV\npopulation is expected to constitute a sizable portion of the light duty\nfleets. This which necessitates controlling the EV charging operations to\nprevent potential grid failures and distribute the resources efficiently. This\nframework leverages pricing dynamics in order to control the EV customer\nrequest rates and to provide a charging service with the best level of quality\nof service. The second framework, on the other hand, is more appropriate for\nsmaller networks, in which the objective is to compute the minimum amount of\nresources required to provide certain levels of quality of service to each\nclass. The results show that the proposed frameworks ensure grid reliability\nand lead to significant savings in capacity planning.\n