This document describes a field validation and verification of the BuildingIQ Predictive Energy Optimization (PEO) technology based on a five-site study. BuildingIQ describes its PEO technology as a software-as-a-service (SaaS) platform that optimizes commercial building HVAC control for system efficiency, occupant comfort, and cost. It is targeted for use in large, complex buildings, and integrates with the building automation system (BAS) to conduct supervisory control. The PEO algorithm defines optimal space air temperature setpoints that are automatically implemented at the variable air volume (VAV) terminal units when possible, or through supply air temperature and duct static pressure setpoints at the air handling unit (AHU) level. The optimization is built upon a learned predictive model that provides a 24-hour ahead forecast of the building’s power profile, using weather forecasts and historical operational data; this model is updated every 4 to 6 hours. Demand-responsive load reductions may also be implemented.
The PEO technology was installed at a five-site cohort that represented climatic diversity, as well as diversity in commercial building types, including offices, a courthouse, a school, and a hospital. The evaluation team conducted an independent assessment of energy savings, according to Option B of the International Performance Measurement and Verification Protocol (IPMVP). Option B quantifies HVAC system energy savings through isolated measures of system load. Cost savings were estimated using a blended estimated cost of electricity from site-specific utility bills, in combination with energy savings. Over an evaluation period than ranged from 7 to 15 months, PEO controls were toggled on and off for one week at a time. The PEO-off periods were taken as the baseline for savings estimates, while the PEO-on periods were taken as the “post-installation” performance period.
To verify that the HVAC energy savings gained from PEO were not achieved at the expense of occupant comfort, three types of analysis were conducted to compare conditions during PEO and conventional control: (1) changes in space conditions (temperature and relative humidity) relative to the ASHRAE thermal comfort zone, (2) changes in stability of space air temperature, and (3) changes in trouble calls documented in facility operations logs.
Factors such as setup and integration effort, tuning and troubleshooting, and impact on building management activities were also evaluated to make conclusions regarding the technology scale-up. These assessments were based on interviews with site points of contact and data tracked throughout the course of the field studies.