Share

Experimental demonstration of model predictive control in a medium sized commercial building.

Number: pap. 3617

Author(s) : LI P., LI D., VRABIE D., et al.

Summary

This paper presents the implementation and experimental demonstration results of a practically effective and computationally efficient model predictive control (MPC) algorithm used to optimize the energy use of the heating, ventilation, and air-conditioning (HVAC) system in a multi-zone medium-sized commercial building. Advanced building control technologies are key enablers for intelligent operations of future buildings, however, adopting these technologies are quite difficult in practice mainly due to the cost-sensitive nature of the building industry. This paper presents the results of implementing optimization-based control algorithm and demonstrates the effectiveness of its energy-saving feature and improved thermal comfort along with lessons-learned. The performance of the implemented MPC algorithm was estimated relative to baseline days (heuristic-based control) with similar outdoor air temperature patterns during the cooling and shoulder seasons (September to November, 2013), and it was concluded that MPC reduced the total electrical energy consumption by more than 20% on average while improving thermal comfort in terms of temperature and maintaining similar zone CO2 levels.

Available documents

Format PDF

Pages: 11 p.

Available

  • Public price

    20 €

  • Member price*

    15 €

* Best rate depending on membership category (see the detailed benefits of individual and corporate memberships).

Details

  • Original title: Experimental demonstration of model predictive control in a medium sized commercial building.
  • Record ID : 30013636
  • Languages: English
  • Subject: Environment
  • Source: 2014 Purdue Conferences. 3rd International High Performance Buildings Conference at Purdue.
  • Publication date: 2014/07/14

Links


See other articles from the proceedings (66)
See the conference proceedings

Indexing