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Hierarchical control of thermostatically controlled loads oriented smart buildings

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  • Xia, Mingchao
  • Song, Yuguang
  • Chen, Qifang

Abstract

With the transition of energy systems, synergetic interaction between consumers and suppliers has been an inevitable trend. As a demand response (DR) resource, thermostatically controlled loads (TCLs) can respond to power fluctuations in power grids caused by renewable energy and load activities by means of TCLs’ characteristics of good thermal energy storage and slow-varying thermal inertia. Aggregating TCLs by clustering methods neglects the coupling of diverse thermal parameters with the scattered geographical locations of controlled TCLs, and will increase the complexity of communication systems and decrease scalability and availability of demand-side scheduling potential. This paper proposes a state transition interval matching (STIM) control strategy and a pinning control method based hierarchical framework. Considering the controlled tendency and compressor lockout of TCLs, STIM strategy achieves unified control of heterogeneous TCLs at the lower layer, which could reduce the relative error caused by a small number of high-power TCLs. Thus, the control accuracy and availability of TCLs’ scheduling potential are enhanced. What’s more, this could help reduce the complexity of communication systems among aggregators and TCLs. At the upper layer, pinning control coordinates the scheduling capacities provided by different buildings in a sparse communication network. This could enhance control stability in the event of a communication fault, and would facilitate the aggregation of newly participating buildings. The feasibility and scalability of TCLs’ participation in DR service are improved by the proposed method of hierarchical control. Finally, the validity of the proposed strategy is verified via comparison with temperature priority list strategy.

Suggested Citation

  • Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919311675
    DOI: 10.1016/j.apenergy.2019.113493
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    References listed on IDEAS

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    Cited by:

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    3. Jahangir Hossain & Aida. F. A. Kadir & Ainain. N. Hanafi & Hussain Shareef & Tamer Khatib & Kyairul. A. Baharin & Mohamad. F. Sulaima, 2023. "A Review on Optimal Energy Management in Commercial Buildings," Energies, MDPI, vol. 16(4), pages 1-40, February.
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    5. Zhang, Anan & Zheng, Yadi & Huang, Huang & Ding, Ning & Zhang, Chengqian, 2022. "Co-integration theory-based cluster time-varying load optimization control model of regional integrated energy system," Energy, Elsevier, vol. 260(C).

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