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The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this article presents an open-source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations.
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E-transit-bench: simulation platform for analyzing electric public transit bus fleet operations
When electrified transit systems make grid aware choices, improved social welfare is achieved by scheduling charging at low grid impact locations and times causing reduced loss, minimal power quality issues and reduced grid stress. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs, etc., that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid’s power flow and therefore cannot account for the power grid’s needs in its day to day operation. In this paper we propose a framework of transportation-grid co-simulation analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day’s traffic from Chattanooga city’s transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to the transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of Transit electrification that further necessitates such an integrated Transportation-Grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.
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- PAR ID:
- 10356662
- Date Published:
- Journal Name:
- Proceedings of the Thirteenth ACM International Conference on Future Energy Systems (e-Energy 2022)
- Page Range / eLocation ID:
- 532 to 541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The ongoing electrification of the transportation fleet will increase the load on the electric power grid. Since both the transportation network and the power grid already experience periods of significant stress, joint analyses of both infrastructures will most likely be necessary to ensure acceptable operation in the future. To enable such analyses, this paper presents an open- source testbed that jointly simulates high-fidelity models of both the electric distribution system and the transportation network. The testbed utilizes two open-source simulators, OpenDSS to simulate the electric distribution system and the microscopic traffic simulator SUMO to simulate the traffic dynamics. Electric vehicle charging links the electric distribution system and the transportation network models at vehicle locations determined using publicly available parcel data. Leveraging high-fidelity synthetic electric distribution system data from the SMART-DS project and transportation system data from OpenStreetMap, this testbed models the city of Greensboro, NC down to the household level. Moreover, the methodology and the supporting scripts released with the testbed allow adaption to other areas where high-fidelity geolocated OpenDSS datasets are available. After describing the components and usage of the testbed, we exemplify applications enabled by the testbed via two scenarios modeling the extreme stresses encountered during evacuations.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1145/3538637.3539586
