Improving the accuracy of energy baseline models for commercial buildings with occupancy data
[2];
- Shanghai Jiao Tong Univ. (China). School of International and Public Affairs; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Division
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Division
- Hong Kong Polytechnic Univ. (China). Dept. of Building and Real Estate
More than 80% of energy is consumed during operation phase of a building's life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. To conclude, the results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); National Natural Science Foundation of China (NSFC); Hong Kong Polytechnic Univ. (China); Rutgers Univ., Piscataway, NJ (United States); International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66
- Grant/Contract Number:
- AC02-05CH11231; 71271184
- OSTI ID:
- 1436599
- Alternate ID(s):
- OSTI ID: 1399815
- Journal Information:
- Applied Energy, Vol. 179, Issue C; ISSN 0306-2619
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Web of Science
Similar Records
Modeling of HVAC operational faults in building performance simulation
Nationwide Energy Saving Potential Evaluation for Office Buildings with Occupant-Based Building Controls