We present a unique virtual testbed that combines a data-plane programmable network emulator and a power distribution system simulator to evaluate smart grid security and resilience applications. The testbed employs a virtual time system for effective simulation synchronization and fidelity enhancement. We showcase the advantages of the simulation testbed through an anomaly detection case study.
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This content will become publicly available on May 1, 2025
GreenEVT: Greensboro electric vehicle testbed
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.
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- NSF-PAR ID:
- 10480518
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE systems journal
- ISSN:
- 1932-8184
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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