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Comparison of model predictive control performance using grey-box and white-box controller models of a multi-zone office building.

Number: pap. 3484

Author(s) : PICARD D., SOURBRON M., JORISSEN F., et al.

Summary

Model Predictive Control (MPC) is a promising control method to reduce the energy use of buildings. Its commercialization is, however, hampered by the dif?culty of obtaining a reliable controller model. This paper compares two approaches to obtain such controller model: (1) a white-box model approach for which a detailed ?rst-principles building model is linearized, and (2) a system identi?cation method using a grey-box model approach. The MPC performance using both model approaches is evaluated on a validated 12 zones model of an existing of?ce building. The results indicate that the MPC performance is very sensitive to the prediction accuracy of the controller model. This paper shows that both approaches can lead to an ef?cient MPC as long as very accurate identi?cation data sets are available. For the considered simulation case, the white-box MPC resulted in a better thermal comfort and used only 50% of the energy used by the best grey-box MPC.

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Pages: 10 p.

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Details

  • Original title: Comparison of model predictive control performance using grey-box and white-box controller models of a multi-zone office building.
  • Record ID : 30019232
  • Languages: English
  • Subject: Environment
  • Source: 2016 Purdue Conferences. 4th International High Performance Buildings Conference at Purdue.
  • Publication date: 2016/07/11

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