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Power Grid Simulation Testbed for Transactive Energy Management Systems

Author

Listed:
  • Ozgur Ozmen

    (Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • James Nutaro

    (Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Michael Starke

    (Electrical and Electronics Systems Research Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Jeffrey Munk

    (Energy and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Larry Roberts

    (Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Xiao Kou

    (Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA)

  • Piljae Im

    (Energy and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Jin Dong

    (Energy and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Fangxing Li

    (Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA)

  • Teja Kuruganti

    (Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Helia Zandi

    (Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

Abstract

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

Suggested Citation

  • Ozgur Ozmen & James Nutaro & Michael Starke & Jeffrey Munk & Larry Roberts & Xiao Kou & Piljae Im & Jin Dong & Fangxing Li & Teja Kuruganti & Helia Zandi, 2020. "Power Grid Simulation Testbed for Transactive Energy Management Systems," Sustainability, MDPI, vol. 12(11), pages 1-19, May.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:11:p:4402-:d:363904
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    References listed on IDEAS

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    1. Nizami, M.S.H. & Haque, A.N.M.M. & Nguyen, P.H. & Hossain, M.J., 2019. "On the application of Home Energy Management Systems for power grid support," Energy, Elsevier, vol. 188(C).
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    Cited by:

    1. Mario Tovar & Miguel Robles & Felipe Rashid, 2020. "PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México," Energies, MDPI, vol. 13(24), pages 1-15, December.

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