Google Nest Learning Thermostat 3rd Gen

(Evaluated by UC Berkeley) An advanced thermostat controls residential and small commercial Heating, Ventilation, and Air Conditioning (HVAC) equipment while communicating with other systems, and uses computational capability to provide advanced functionality, such as including additional sensors, the ability to group multiple thermostats, energy reports, and/or notifications.

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Technology Basics Application Guidance Energy & Cost Impacts

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Google Nest Learning Thermostat 3rd Gen

The Google Nest thermostat supports up to three heating/two cooling stages (conventional), and two heating/cooling stages with auxiliary heat (heat pumps). Nest learns temperature preferences to create a schedule and has an on-board occupancy sensor. Its Rush Hour Rewards program enables participation in utility demand response. Nest connects through Wi-Fi.

Hub Highlights:

On-board motion (occupancy) sensor and outdoor temperature through Internet weather
Pairs with other systems (cameras etc)

Model Number	T3007ES
Primary Setting	Residential
User Interface Options	Mobile app (Nest)
Multiple Thermostat Control	N/A
Access Restriction	Can lock heat or cool temperature settings to prevent others from changing settings or changing the temperature outside of a restricted range
Notifications/Reports	Alerts (heat/cooling not working, power failure, filter) Energy reports
Available Sensors	On-board relative humidity and motion (occupancy) sensor Outdoor temperature through Internet weather Pairs with other systems (cameras etc)
Demand Response Capable	Can participate in Utility Demand Response programs; Open Automated Demand Response (OpenADR) capable

Last Edited on: 07/2023

Model	T3007ES
Sample Size	1
Thermal sensor accuracy (@68F)	2.7±0.3 °F
Thermal sensor accuracy (@75F)	2.6±0.1 °F
Impact of surrounding surface temperature on Thermal sensor accuracy	Very good
Standby power	0.09 W

Last Edited on: 10/03/24

Data Collection

The technology evaluation team performed a heuristic evaluation of basic thermostat modes of operation (turning on, changing setpoint, reading display) for each of the tested products. In heuristic evaluations assess user interfaces according to guidelines for the design of user-friendly systems.

Sample Size

Estimated Usability

Good: likely good usability in most tasks; Fair: likely fair usability in most tasks.

Fair