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A fully distributed optimal control approach for multi-zone dedicated outdoor air systems to be implemented in IoT-enabled building automation networks

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  • Li, Wenzhuo
  • Wang, Shengwei

Abstract

For heating, ventilation and air-conditioning (HVAC) systems, centralized optimal control approaches are widely investigated, while hierarchical distributed optimal control approaches are of increasing attention. Using both approaches, the central station and the coordinating agent play critical roles, resulting in low robustness. A novel fully distributed approach may offer higher robustness, but has not yet been investigated for HVAC systems. This paper therefore proposes a fully distributed optimal control approach for multi-zone dedicated outdoor air systems (DOASs) to be implemented in IoT-enabled building automation networks. Without the coordinating agent, information is exchanged directly between connected agents. The optimal solutions are found by coordinating these multiple agents. During iterations, the outdoor air volume of individual rooms and the PAU are optimized locally using the Incremental Cost Consensus (ICC) algorithm, and the outdoor air volume mismatch is estimated locally using the average consensus algorithm. Tests are conducted to validate the proposed approach by comparing it with existing approaches. The impacts of communication topology on the performance of the proposed approach are investigated. Results show that the proposed fully distributed optimal control approach with the fully connected topology performs better than the existing hierarchical distributed approach. Among different communication topologies, the proposed approach with the fully connected topology had the highest robustness, lowest computation complexity and highest optimization efficiency. It also guaranteed the best control performance when deployed over physical platforms (e.g. IoT-based smart sensors of limited capacity), which limit the maximum iteration number.

Suggested Citation

  • Li, Wenzhuo & Wang, Shengwei, 2022. "A fully distributed optimal control approach for multi-zone dedicated outdoor air systems to be implemented in IoT-enabled building automation networks," Applied Energy, Elsevier, vol. 308(C).
  • Handle: RePEc:eee:appene:v:308:y:2022:i:c:s0306261921016421
    DOI: 10.1016/j.apenergy.2021.118408
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Jiang, Yuliang & Zhu, Shanying & Xu, Qimin & Yang, Bo & Guan, Xinping, 2023. "Hybrid modeling-based temperature and humidity adaptive control for a multi-zone HVAC system," Applied Energy, Elsevier, vol. 334(C).
    3. Esmaeilzadeh, Ahmad & Deal, Brian & Yousefi-Koma, Aghil & Zakerzadeh, Mohammad Reza, 2023. "How combination of control methods and renewable energies leads a large commercial building to a zero-emission zone – A case study in U.S," Energy, Elsevier, vol. 263(PD).
    4. Andrzej Ożadowicz, 2023. "Technical, Qualitative and Energy Analysis of Wireless Control Modules for Distributed Smart Home Systems," Future Internet, MDPI, vol. 15(9), pages 1-21, September.
    5. Li, Wenzhuo & Tang, Rui & Wang, Shengwei & Zheng, Zhuang, 2023. "An optimal design method for communication topology of wireless sensor networks to implement fully distributed optimal control in IoT-enabled smart buildings," Applied Energy, Elsevier, vol. 349(C).

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