Northwestern University SQBRC: Data-Driven Validation of High-Performance Design
The presentation focuses on an in-depth energy performance analysis of the first phase of Northwestern University's new Simpson Querrey Biomedical Research Center (SQBRC). Included in the first phase is the design and construction of 629,000 square feet, accommodating a vivarium, and 13 levels above-grade containing nine research floors, three mechanical floors, a lobby, winter garden, 140-seat lecture hall, collaboration space, conference space, offices, and six floors of shell space for future use.
Areas of focus include:
- Preprocessing of Metered Data: The process of converting raw data into usable knowledge was an integral part of this analysis and will be outlined in a sufficiently general way to allow for it to be leveraged by others.
- Leveraging Data from Multiple Sources: Data was integrated from monthly Utility bills, building automations system (BAS) trends for fragments of time, submetered data at 5-minute intervals, etc. Merging these data sources into one complete and accurate picture was critical.
- Advanced Visualization: Microsoft's Power BI platform was used to carry out advanced analytics as well as generate interactive visualizations.
The key takeaway from our analysis was that metered source energy use intensity is 363 kBtu/sf/yr, which is right in line with the design model's anticipated value of 347, and substantially less than the baseline source energy use intensity of 512. As the numbers show, SQBRC is operating at or very near the lofty performance goals put forth during design.
- Be able to preprocess readily available metered data more effectively;
- Better understand proper design and optimization of heat recovery chillers;
- Identify areas where analytics can be used to augment available data and transform incomplete data into meaningful information; and
- Understand the power of dynamic and interactive data visualization to more effectively present findings.
Steve leads the Chicago Office's high performance design team. He brings extensive knowledge of energy modeling, Life cycle cost analysis, data analytics (including supervised and unsupervised machine learning), and advanced visualization which he employs with great effect on his clients' projects.
Mr. Baehr serves as a Senior Project Manager at Evanston's world renowned Northwestern University. Jay's career at Northwestern started back in 1999 and has since gone on to cover more than 20 years of successful project management. His formal training lies in Architecture where he obtained a bachelors degree from the University of Cincinnati.
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