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Large-scale Testbed

The Large-scale Testbed (LTB) is a tightly integrated, closed-loop platform for rapid prototyping of power systems. ANDES, AMS, DiME, and AGVis are four major independent sub packages of LTB that serve as a dynamic simulator, market simulator, distributed messaging environment, and grid visualizer, respectively. Towards a one-stop solution, these LTB packages can serve for both individual and federated use.

AMS is included in the newly released v2.0.

Why LTB

LTB platform enables power system dynamic simualiton, market simulation, geographical visualization, real-time simualtion, and dispatch-dynamic co-simulaiton.

Getting trouble with dispatch in a dynamic simulation? The interoperability of ANDES for scheduling supports secured dispatch in a dynamic simulation.

Getting lost in the APIs of simulators? Easy-to-use ANDES and AMS can be your last stop to prototype new algorithms and models.

Looking for a geographical visualization? AGVis allows geographical visualization with multiple options.

Interested in a real-time closed-loop simulation? LTB has integrated simulators and communication environments.

Video list:

LTB is currently under active development. Welcome to join the Discussion of LTB.

Citing LTB

If you use LTB packages for research or consulting, we kindly request you to cite the following papers in your publication that uses LTB

F. Li, K. Tomsovic and H. Cui, "A Large-Scale Testbed as a Virtual Power Grid: For Closed-Loop Controls in Research and Testing," in IEEE Power and Energy Magazine, vol. 18, no. 2, pp. 60-68, March-April 2020, doi: 10.1109/MPE.2019.2959054.
H. Cui, F. Li and K. Tomsovic, "Hybrid Symbolic-Numeric Framework for Power System Modeling and Analysis," in IEEE Transactions on Power Systems, vol. 36, no. 2, pp. 1373-1384, March 2021, doi: 10.1109/TPWRS.2020.3017019.

Who is using LTB

Natinoal Science Foundation US Department of Energy CURENT ERC Oklahoma State University Lawrence Livermore National Laboratory Idaho National Laboratory

Sponsors and developers

This work was supported in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program.

ANDES is authored by Hantao Cui, AMS is authored by Qiwei Zhang, DiME and AGVis are developed and maintained by Nicholas West and Nicholas Parsly.

License

LTB is licensed under the GPL v3 License.