The overall goal of this Project was to create a new occupant-based paradigm for Heating, Ventilation, and Air Conditioning (HVAC) control that will reduce HVAC energy use in buildings while improving occupant comfort. The Project explored integrating low-energy personal comfort systems (PCS) into HVAC operations, advanced variable-air volume (VAV) control algorithms, and innovative open-source software for monitoring and control. The Project investigated deployment of commercially available occupant-vote based ambient temperature control technology alongside the other innovations. To accomplish this the research team developed, tested and demonstrated, through the performance of three detailed case studies, new products and HVAC control & operation practices, and performed work to identify market transformation potential for these innovative technologies in standards, codes, and common practice. Key research activities and findings are summarized below.• Fifty low-energy heated and cooled chairs (PCS) with wireless internet connectivity were designed and fabricated for use in the demonstration field studies.• A method of test using a thermal manikin was developed to determine personal heater efficiency (PHE). Experiments on 12 personal heaters found that conductive heaters (heated chairs or foot-warmers) are far more efficient than radiant or convective heaters. • Three demonstration field studies were conducted to study the project innovations. Two were in office buildings with conventional VAV reheat with overhead air distribution: (1) San Mateo County (SMC) office building in Redwood City, and (2) Sutardja Dai Hall (SDH) on the UC Berkeley campus. A third was in an office building with advanced low-energy space conditioning: (3) Integral Group office building in San Jose, which uses radiant slab heating and cooling.• The SMC field study involved PCS chairs alongside occupant vote-based HVAC control (Comfytm). Key results showed that the PCS chair users have high thermal satisfaction across the investigated setpoint range of 20.5-24.5°C (69-76°F). Occupant and management response to voting-based temperature control (Comfytm) was positive, although we were unable to directly confirm energy use reduction resulting from expanded temperature deadbands.• The SDH field study focused on implementation and testing of advanced VAV control strategies in combination with occupant vote-based HVAC control. Detailed field trials were completed for two promising advanced VAV control strategies: (1) time-averaged ventilation (TAV) and (2) cost-based supply air temperature (SAT) reset. TAV testing showed a reduction in fan (15%), reheat (41%), and chilled water (23%) energy. A cost-based SAT reset testing showed an additional reduction in total HVAC energy costs of 29%.• The most successful energy-saving and immediately applicable innovative technology demonstrated in the Project was time-averaged ventilation (TAV) for VAV reheat air distribution systems. As a result, TAV has been incorporated in ASHRAE Guideline 36, which when published later in 2017, will reach a wide audience and encourage widespread adoption.• Innovative open-source software can enable the development and integration of the occupant-based HVAC technologies explored by this Project. Applications included the connectivity of PCS chairs, underlying technology for commercially available occupant voting-based temperature control, and deployment of advanced VAV control algorithms.• The research team evaluated and identified code change potential for Personal Comfort Systems and VAV controls at both the state energy code level (Title 24 Building Energy Efficiency Standards, Title 20 Appliance Efficiency Standards), as well as national energy and comfort standards (ASHRAE Standards 90.1, 189.1 and 55).
[1]
David E. Culler,et al.
BTrDB: Optimizing Storage System Design for Timeseries Processing
,
2016,
FAST.
[2]
Hui Zhang,et al.
EXTENDING AIR TEMPERATURE SETPOINTS: SIMULATED ENERGY SAVINGS AND DESIGN CONSIDERATIONS FOR NEW AND RETROFIT BUILDINGS
,
2015
.
[3]
Therese Peffer,et al.
Getting into the zone: how the internet of things can improve energy efficiency and demand response in a commercial building
,
2016
.
[4]
Therese Peffer,et al.
Writing controls sequences for buildings: from HVAC industry enclave to hacker's weekend project
,
2016
.
[5]
Paul Raftery,et al.
Time-averaged ventilation for optimized control of variable-air-volume systems
,
2017
.
[6]
Weimin Wang,et al.
Energy Savings Modeling of Standard Commercial Building Re- tuning Measures: Large Office Buildings
,
2012
.
[7]
Kwang Ho Lee,et al.
Energy savings from extended air temperature setpoints and reductions in room air mixing - eScholarship
,
2005
.
[8]
Stefano Schiavon,et al.
Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures
,
2013
.
[9]
David E. Culler,et al.
XBOS: An Extensible Building Operating System
,
2015
.
[10]
Hui Zhang,et al.
Well-connected microzones for increased building efficiency and occupant comfort - eScholarship
,
2016
.
[11]
Gail Brager,et al.
Developing an adaptive model of thermal comfort and preference
,
1998
.
[12]
Sebastian A.C. Cohn.
Development of a Personal Heater Efficiency Index
,
2017
.