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Identification for model based predictive control applied to an office building with a thermally activated building systems.

Number: pap. 342

Author(s) : ZACEKOVA E., VANA Z., VERHELST C., et al.

Summary

In recent years, the number of applications that use advanced control algorithms such as Model Predictive Control (MPC) for building climate control is increasing. These control strategies provide a substantial savings potential, but for their optimal behaviour it is necessary to have a good mathematical model of the building. Creation of a mathematical model appropriate for MPC is a delicate task. This is especially the case of real applications, characterized by a lack of available measurements and by poor quality data. This paper presents a system identification (SI) procedure to obtain a building model based on real measurement data. The innovative character of the presented SI method is mainly the choice of the identification procedure cost function - multi-step prediction error criterion - which directly corresponds to the MPC cost function. The resulting model is suitable for use within the MPC framework, where the model should be accurate even during long time horizons. Being used within the MPC, such a model outperforms classically identified models based on one-step prediction error minimization. The procedure is illustrated for the Hollandsch Huys building, a 3-storey office building, which is monitored and studied in the framework of the Geotabs project.

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Pages: 10 p.

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Details

  • Original title: Identification for model based predictive control applied to an office building with a thermally activated building systems.
  • Record ID : 30008884
  • Languages: English
  • Subject: Environment
  • Source: Clima 2013. 11th REHVA World Congress and 8th International Conference on Indoor Air Quality, Ventilation and Energy Conservation in Buildings.
  • Publication date: 2013/06/16

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