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.
more »
« less
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.
more »
« less
- 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
More Like this
-
-
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.more » « less
-
As the number of electric vehicles (EVs) within society rapidly increase, the concept of maximizing its efficiency within the electric smart grid becomes crucial. This research presents the impacts of integrating EV charging infrastructures within a smart grid through a vehicle to grid (V2G) program. It also observes the circulation of electric charge within the system so that the electric grid does not become exhausted during peak hours. This paper will cover several different case studies and will analyze the best and worst scenarios for the power losses and voltage profiles in the power distribution system. Specifically, we seek to find the optimal location as well as the ideal number of EVs in the distribution system while minimizing its power losses and optimizing its voltage profile. Verification of the results are primarily conducted using GUIs created on MATLAB. These simulations aim to develop a better understanding of the potential impacts of electric vehicles in smart grids, such as power quality and monetary benefits for utility companies and electric vehicle usersmore » « less
-
The development of new technologies is increasing transportation electrification and electric vehicles (EVs) are expected to become even more popular in coming years. High EV adoption rates can increase the potential to use EVs as an energy resource and operate in vehicle-to-grid (V2G) and vehicle-to-home (V2H). This paper focuses on the resilience analysis of using EVs and roof-top solar photovoltaic systems (PVs) to provide power support in network microgrids (MGs) experiencing an outage due to extreme weather conditions. To determine the effectiveness of using EVs and PVs as backup energy resources, a set of resilience metrics are evaluated for different cases and duration. Simulation results show that the management of EVs and PVs in residential networked MGs could provide power support for several hours during the restoration of a distribution system experiencing an outage.more » « less
-
more » « less
Recent advances in multi-rotor vehicle control and miniaturization of hardware, sensing, and battery technologies have enabled cheap, practical design of micro air vehicles for civilian and hobby applications. In parallel, several applications are being envisioned that bring together a swarm of multiple networked micro air vehicles to accomplish large tasks in coordination. However, it is still very challenging to deploy multiple micro air vehicles concurrently. To address this challenge, we have developed an open software/hardware platform called the University at Buffalo’s Airborne Networking and Communications Testbed (UB-ANC), and an associated emulation framework called the UB-ANC Emulator. In this paper, we present the UB-ANC Emulator, which combines multi-micro air vehicle planning and control with high-fidelity network simulation, enables practitioners to design micro air vehicle swarm applications in software and provides seamless transition to deployment on actual hardware. We demonstrate the UB-ANC Emulator’s accuracy against experimental data collected in two mission scenarios: a simple mission with three networked micro air vehicles and a sophisticated coverage path planning mission with a single micro air vehicle. To accurately reflect the performance of a micro air vehicle swarm where communication links are subject to interference and packet losses, and protocols at the data link, network, and transport layers affect network throughput, latency, and reliability, we integrate the open-source discrete-event network simulator ns-3 into the UB-ANC Emulator. We demonstrate through node-to-node and end-to-end measurements how the UB-ANC Emulator can be used to simulate multiple networked micro air vehicles with accurate modeling of mobility, control, wireless channel characteristics, and network protocols defined in ns-3.
