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Analysis of Indoor Environmental Conditions and Electricity Savings Using a Smart Thermostat

Analysis of Indoor Environmental Conditions and Electricity Savings Using a Smart Thermostat

From ASHRAE Journal Newsletter, May 12, 2020

Internet-connected smart thermostats optimize settings that could save HVAC system energy use, which can lead to cost savings.

A recent Science and Technology for the Built Environment article discusses the results of an analysis using smart thermostat data. The analysis measured electricity savings and indoor environmental conditions zone by zone using a smart thermostat that included temperature and occupancy data from each zone in a single-family residence.

Researchers Sukjoon Oh, Associate Member ASHRAE; Jeff S. Haberl, Ph.D., Fellow ASHRAE; and Juan-Carlos Baltazar, Ph.D., Member ASHRAE, discuss the paper.

1. What is the significance of this research?

This research is significant because this is one of the first studies to show measured savings from the installation of the smart thermostat with temperature and occupancy sensors in a residence.

2. Why is it important to explore this topic now?

Previous studies have claimed that smart meters and smart home technologies can provide benefits to utilities by reducing their electric demand. This research presented the results of an analysis of measured, zone-by-zone indoor environmental conditions and electricity savings from the use of a smart thermostat that includes temperature and occupancy data from each zone in a single-family residence. The hourly interval data from a smart meter was also used. In this analysis, statistical indoor air temperature profiles were developed for each zone before and after the installation of the smart thermostat, which shows the change of the indoor/outdoor temperature profiles of each zone in the residence.

3. What lessons, facts and/or guidance can an engineer working in the field take away from this research?

The results showed that the use of temperature and occupancy sensor controls available from a smart thermostat produced significant changes to the indoor air temperature profiles in each zone. In addition, it was observed that large variations in the measured indoor air temperatures from each zone were not represented by the indoor air temperature at the location of the thermostat. The changes to the before-after indoor air temperature profiles from each zone also presented new challenges to simulating the annual savings with a calibrated building energy simulation model.

The results also showed that the case-study residence with a single-zone HVAC system controlled by a single thermostat that was retrofitted with wireless occupancy and temperature sensors in each zone achieved significant energy savings for the homeowner. The measured savings were 496 kWh (37.9 %), and the annual estimated savings was 5,208 kWh (43.6 %). When the costs of the new thermostat ($249) with the seven remote temperature and occupancy sensors ($237), including the installation fee ($100), were considered (i.e., the total cost of $586), a simple payback period was approximately 1.0 year because the annual total cost saving was $602.

4. How can this research further the industry's knowledge on this topic?

Based on the results of this single residence, it was found that the methodology of this research is appropriate to use for other similar studies. Although the study included one residence, the methods developed are generic, so the results of this research will be valid for a broad class of single-family residences that are retrofitted with a smart thermostat using remote temperature and occupancy sensors. This research shows detailed, clear insights about the dynamics occurring in every zone of the case-study residence using well-established, statistical methods for analyzing time-series data. The approaches used in this research are useful to analyze the dynamics of building operation in different zones in a residence using the smart thermostat, which the previous studies did not provide.

5. Were there any surprises or unforeseen challenges for you when preparing this research?

First, there was a challenge regarding sensor locations. It was hard to decide where the temperature and occupancy sensors should be located in each zone of the case-study residence. Different sensor locations could affect the results. Second, analyzing more personalized thermal comfort such as relative humidity in each zone was a challenge.

Finally, the intervals of the measured data were important. For example, to enhance accuracy, the one-minute interval occupancy data should be used because the five-minute interval sensors could not accurately detect when an occupant moved to different rooms. In addition, the same time interval should be used across different devices because analyzing the different intervals of the data between different devices was challenging. As a result, a minute-by-minute analysis is recommended; however, this will require additional cost. These three challenging issues will be handled in a future study to improve this research.