Previous demonstrations of OBCC technology for guest rooms in the U.S.
Therefore, this paper presents results from a detailed energy savings analysis of an OBCC technology in guest rooms by developing a calibrated building energy simulation based on one year of detailed energy, indoor environmental quality (IEQ), and occupancy measurements of 14 guest rooms in the case-study hotel building in Washington, DC.
This study reviews five previous field tests that measured HVAC and/or lighting energy savings from the deployment of an OBCC technology in guest rooms in the U.S., mainly in California, including those by Lau (2000), Pistochini et al.
In summary, previous field studies have reported the energy savings of OBCC technology based on simple side-by-side tests (i.e., parallel approach) or before-and-after tests (i.e., series approach) using a small sample size of guest rooms for both card-key-and occupancy-sensor-based systems that were not integrated with the hotel's PMS.
ANALYSIS OF THE ENERGY PERFORMANCE OF AN OBCC TECHNOLOGY
This process reduced uncertainties and improved the accuracy of the energy savings assessments of the OBCC control algorithms that were being tested.
Therefore, higher savings are expected from the application of OBCC technology to guest rooms that include OA ventilation controls, which are required to comply with the latest edition of ASHRAE/IES Standard 90.1 (ASHRAE 2016).
from the deployment of an OBCC technology in hotel guest rooms by developing a calibrated building energy simulation based on one-year ofdetailed energy, IEQ, and occupancy measurements of the 14 guest rooms on the sixth floor of the case-study hotel building in Washington, DC, from June 2015 to May 2016.
Base Case 3 Test Case 1 Test Case 2 Test Case 3 Total Floor 13.80 11.63 12.10 11.74 VRF Outdoor Unit 6.40 4.55 5.01 4.66 VRF Indoor Unit 0.73 0.48 0.49 0.48 DOAS 4.20 4.11 4.11 4.11 Lights 0.68 0.68 0.68 0.68 Plug Load 1.80 1.80 1.80 1.80 Unmet Hours (%) 0.0% 6.5% 5.0% 5.7% A review of the previous demonstrations of OBCC technology for guest rooms found the key influential factors affecting the performance of the OBCC technology (i.e., room occupancy profiles, guests' preferred temperatures/behaviors, and internal heat gains) were not properly adjusted in the previously reported savings, which resulted in large variations and uncertainties in the reported savings.
The results shows the energy savings of the OBCC control algorithm installed at the case-study hotel with VRF set points reset to 15.6[degrees]C (60[degrees]F) for heating and26.7[degrees]C (80[degrees]F) for cooling when the room was unoccupied for both sold and unsold rooms were 15.8% for the total floor and 29.4% of total VRF heating and cooling energy use with a 6.5% increase in occupied unmet hours.