Paper Conference

Proceedings of Building Simulation 2021: 17th Conference of IBPSA

     

The impact of occupancy prediction accuracy on the performance of model predictive control (MPC) in buildings

Tao Yang, Fisayo Caleb Sangogboye, Krzysztof Arendt, Konstantin Filonenko, Jonathan Dallaire, Mikkel Baun Kjærgaard, Christian Veje
Center for Energy Informatics, University of Southern Denmark, Denmark

DOI: https://doi.org/10.26868/25222708.2021.30571
Abstract: Model Predictive Control (MPC) is a promising approach for mitigating energy consumption and for enabling efficient building climate regulation without sacrificing occupants’ comfort. At the same time, occupancy is one of the leading factors influencing the performance of MPC. In this paper, we investigate the impact of occupancy prediction accuracy on the performance of building MPC in terms of energy consumption and thermal discomfort. The obtained results indicate that MPC consumes more energy than conventional rulebased controllers. Occupancy predictions with low accuracy (prediction error) can lead to lower energy consumption at the expense of comfort violations. However, the result also indicates that the negative influence of prediction error can be partially mitigated by adopting longer optimization horizons.
Keywords: Occupancy prediction, Model predictive control, Optimization, HVAC
Pages: 3560 - 3567
Paper:
bs2021_30571