Name
Abstract | ||
|---|---|---|
Intelligent control of heating, ventilation, and air conditioning (HVAC) systems in commercial buildings have been extensively studied in the literature. Although prior work has shown the benefits of using Model Predictive Control (MPC), existing work falls short either by relying on linear HVAC models or using MPC assuming control actions at a single (hourly) time scale, although more frequent control is feasible for some HVAC elements. Our main contribution is the use of a bi-linear thermal model and the careful modeling of the multiple time-scales inherent in the operation of an HVAC system, which permits the design of a multiple time-scale MPC control. We find that employing a multiple time-scale MPC results in significantly better comfort in comparison to a single time-scale MPC, typically without an increase in power consumption. Moreover, there exist cases where there is a significant reduction in power consumption (40%) for the two time-scale MPC in comparison to the single time-scale, with no decrease in comfort. |
Year | Venue | Field |
|---|---|---|
2016 | e-Energy (Posters) | Intelligent control,Scale model,Air conditioning,Ventilation (architecture),Control theory,HVAC,Model predictive control,Harmonics,Thermal comfort,Engineering |
DocType | Citations | PageRank |
Conference | 1 | 0.36 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rachel K. Kalaimani | 1 | 6 | 2.24 |
| Srinivasan Keshav | 2 | 3778 | 761.32 |
| Catherine Rosenberg | 3 | 66 | 10.71 |