Google Nest GA05###-** Information
| Thermostat | Google Nest Google Nest Learning Thermostat |
| Model Number | GA05###-** |
| Root Product Name | Google Nest GA05- |
| Additional Info | ,GA05169-US,; ,GA05171-US,; ,GA05551-US,; ,GA05557-US,; ,GA05560-US,; ,GJQ8U, |
| Brand Owner | Google LLC |
| Brand Name | Google Nest |
| Model Name | Google Nest Learning Thermosat |
| Sold In | United States, Canada |
| Additional Device Model Numbers | GJQ8U GA05169-US GA05171-US GA05551-US GA05557-US GA05560-US |
| Device Family ID | FAM_1073133_042420242023161_3111631 |
| UPC | 193575038469;193575038476;193575038483;193575038490;193575038506 |
| Date On Market | August 6, 2024 |
| Date Qualified | April 24, 2024 |
| Model ID | ES_1073133_GA05###-**_042320241603677_4143935 |
| PD ID | 3462877 |
Thermostat Features
| Static Temperature Accuracy (Deg. F) | 0.09 |
| Time To Enter Standby After Interaction (seconds) | 20.4 |
| Heating And Cooling Features | External Temperature Detection,Time of Day Usage,Geofencing (User Device Based),Humidity Sensing,Occupancy Sensor on Device |
| Demand Response Summary | Google Nest thermostats support a variety of Demand Response (DR) services, including dispatchable peak load management, and emergency (fast-response) dispatch. Nest offers a comprehensive DR solution in which Nest's cloud-based server acts as an OpenADR-compliant "Virtual End Node" for a DR signal from a Load Management Entity, and upon receipt of that signal executes customized DR algorithms on each participating device (as a "Virtual Top Node"). Devices can be grouped at the discretion of the Load Management Entity for locational dispatch. An API is available for direct integration with popular Demand Response Management Systems for dispatch. Comprehensive aggregated reporting is provided to the Load Management Entity for measurement and verification purposes, including load reduction estimates and the impact of device adjustments by interval. Google Nest's DR solutions are specifically designed to optimize participant satisfaction through the use of pre-conditioning (where applicable) and personalized schedule adjustments to ensure occupant comfort by limiting deviations from scheduled setpoints. In addition, the user can opt out any time. The algorithms are regularly updated and enhanced based on operational experience and user feedback. |
Networking Features
| Network Standby Average Power Consumption (watts) | 0.1 |
| Communication Method | Bluetooth,Other,Wi-Fi |
| Secondar Communication Method | Thread |
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