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Energy efficient climate control in office buildings without giving up implementability

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  • Gruber, Mattias
  • Trüschel, Anders
  • Dalenbäck, Jan-Olof

Abstract

The adaptation between a building and its automation system can potentially be increased by model-based controllers with an integrated control model and information about indoor climate disturbances. The associated energy savings potential is large but a widespread utilization is typically prevented by high complexities. From that point of view, a trade-off technology that combines implementability with an overall higher performance than the system of current practice would be a better option at most sites. This work presents an experimental evaluation of an alternative controller that follows the same principle as model-based, but has gone through a large number of simplification measures for a reduced overall complexity and a limited function. The controller was evaluated for indoor climate control by automating the ventilation flow rate during a typical office working day that was re-created in a laboratory environment. Experiments were conducted in two different office sites, as well as during two weather seasons of Swedish summer and winter. From the investigation, it was concluded that despite of the reduced complexity, the investigated controller could save between 12% and 19% of indicated energy compared to a system of common practice at the same time as the quality of indoor climate was maintained.

Suggested Citation

  • Gruber, Mattias & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Energy efficient climate control in office buildings without giving up implementability," Applied Energy, Elsevier, vol. 154(C), pages 934-943.
    • Handle: RePEc:eee:appene:v:154:y:2015:i:c:p:934-943
    DOI: 10.1016/j.apenergy.2015.05.075
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    1. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
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    3. Goyal, Siddharth & Ingley, Herbert A. & Barooah, Prabir, 2013. "Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance," Applied Energy, Elsevier, vol. 106(C), pages 209-221.
    4. Žáčeková, Eva & Váňa, Zdeněk & Cigler, Jiří, 2014. "Towards the real-life implementation of MPC for an office building: Identification issues," Applied Energy, Elsevier, vol. 135(C), pages 53-62.
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    Cited by:

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    7. Ma, Jun & Cheng, Jack C.P., 2016. "Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology," Applied Energy, Elsevier, vol. 183(C), pages 182-192.
    8. Cui, Hongzhi & Tang, Waiching & Qin, Qinghua & Xing, Feng & Liao, Wenyu & Wen, Haibo, 2017. "Development of structural-functional integrated energy storage concrete with innovative macro-encapsulated PCM by hollow steel ball," Applied Energy, Elsevier, vol. 185(P1), pages 107-118.
    9. Ghahramani, Ali & Zhang, Kenan & Dutta, Kanu & Yang, Zheng & Becerik-Gerber, Burcin, 2016. "Energy savings from temperature setpoints and deadband: Quantifying the influence of building and system properties on savings," Applied Energy, Elsevier, vol. 165(C), pages 930-942.
    10. Rehman, Hassam Ur, 2017. "Experimental performance evaluation of solid concrete and dry insulation materials for passive buildings in hot and humid climatic conditions," Applied Energy, Elsevier, vol. 185(P2), pages 1585-1594.

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