Improving Critical Buildings Energy Resilience via Shared Autonomous Electric Vehicles — a Sequential Optimization Framework
Publication Year: 2024
Author(s): Liu J, Abdin A, Puchinger J
Abstract:
The growing interdependence between electric power systems and transportation systems is largely due to the widespread adoption of electric vehicles (EVs) and their charging infrastructures. EVs can add additional load to the power system but also contribute to efficient and resilient operations by providing back power when not in use. The Vehicle-to-Grid (V2G), Vehicle-to-Building (V2B), and Vehicle-to-X (V2X) capabilities of EVs have been extensively studied. However, the development of autonomous driving systems and their integration into sharing mobility services is less studied. Shared autonomous electric vehicles (SAEVs) could allow for more control over the actions of the fleet, allowing for large-scale coordinated responses both to mobility and energy demands. This coordinated response can be particularly useful for providing emergency power services in case of power loss while maintaining a high level of transportation service. Thus improving the overall resilience of the system. The study presents a dynamic optimization framework for assessing the potential of the SAEV fleet to enhance energy resilience in critical buildings through V2B services. Power outage scenarios for critical buildings are considered, and the potential of the SAEV fleet to fully or partially respond to the emergency power outage is studied. In addition, sensitivity analysis for key parameters, such as the outage parameters, is introduced. The results of the case study for the Ile-de-France region in France show that the SAEV fleet has the potential to provide V2B service for critical buildings at an acceptable loss of passenger total waiting time on the transportation side. Furthermore, it is shown that it is capable of satisfying the emergency power load at a lower cost compared to investing in extra backup generators unless the outage occurs at significantly high frequencies.
Source of Publication: Computers & Operations Research
Vol/Issue: 163: 106513
DOI No.: 10.1016/j.cor.2023.106513
Country: China
Publisher/Organisation: Elsevier
Rights: Elsevier Ltd.
URL:
https://sciencedirect.com/science/article/abs/pii/S0305054823003775
Theme: Vehicle Technology | Subtheme: Electric vehicles
Related Documents
Journals
World Electric Vehicle Journal
Published Year: 2007
Abstract:
The World Electric Vehicle Journal is the first peer-reviewed international scientific journal... Read More
Journals
International Journal of Electric And Hybrid Vehicles
Published Year: 2007
Abstract:
International Journal of Electric and Hybrid Vehicles (IJEHV) is a quarterly publication and p... Read More