Roshany-Yamchi, Samira , Witheepanich, Kritchai , ESCAÑO GONZÁLEZ, JUAN MANUEL, McGibney, Alan , Rea, Susan

No

International Conference On System Theory Control And Computing

Proceedings Paper

Científica

✗

✗

01/01/2017

000427419900107

Distributed model predictive control (DMPC) for thermal regulation in multi-zone buildings continues to gain attention over centralized approaches. Particularly, centralized control approaches have been shown to become impractical when applied to large-scale buildings due to for example, computation complexity, modeling complexity of large buildings and availability of required sensor and actuator infrastructure. In this paper a novel selective DMPC algorithm is developed in which, each agent optimizes a cost function to minimize the control effort in order to save energy and satisfying the comfort bound. The proposed method is useful especially in building thermal regulation when the objective is to keep the temperature of each zone in the building within the defined comfort bound.

Distributed Model Predictive Control; Soft Constraint; Building Energy Management; Energy Optimization