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Comparative study of neighbor communication approaches for distributed model predictive control in building energy systems

Author

Listed:
  • Baranski, Marc
  • Meyer, Lina
  • Fütterer, Johannes
  • Müller, Dirk

Abstract

Model predictive control (MPC), although considered a high-potential control approach, usually requires considerable effort for model-creation and parametrization. Moreover, many models can be too computationally intensive for control applications. Distributed model predictive control (DMPC) is a promising approach that avoids the construction of a complex model of the total system and thus facilitates modeling and supports the use of exact simulation models.

Suggested Citation

  • Baranski, Marc & Meyer, Lina & Fütterer, Johannes & Müller, Dirk, 2019. "Comparative study of neighbor communication approaches for distributed model predictive control in building energy systems," Energy, Elsevier, vol. 182(C), pages 840-851.
    • Handle: RePEc:eee:energy:v:182:y:2019:i:c:p:840-851
    DOI: 10.1016/j.energy.2019.06.037
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    Cited by:

    1. Tang, Zihan & Wu, Xiao, 2023. "Distributed predictive control guided by intelligent reboiler steam feedforward for the coordinated operation of power plant-carbon capture system," Energy, Elsevier, vol. 267(C).
    2. Maier, Laura & Schönegge, Marius & Henn, Sarah & Hering, Dominik & Müller, Dirk, 2022. "Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings," Applied Energy, Elsevier, vol. 326(C).
    3. Joe, Jaewan & Im, Piljae & Cui, Borui & Dong, Jin, 2023. "Model-based predictive control of multi-zone commercial building with a lumped building modelling approach," Energy, Elsevier, vol. 263(PA).

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