Google Inc.

Allen Joseph Minich

Yoky Matsuoka

Mark Rajan Malhotra

Mark D Stefanski

Joseph Adam Ruff

Todd Andrew Hester

Jonathan Crimins

Scott Ruffner

Amanda Sahl

Michael D Dixon

Yash Modi

George Alban Heitz

Todd Hester

Praveen Subramani

Scott A McGaraghan

William Greene

Kara Malhotra

A control system includes an energy management system in operation with intelligent, network-connected thermostats located in structures. The thermostats are operable to control heating, ventilation, and air conditioning (HVAC) systems. Control during a demand response (DR) event period may be performed based on an optimal control trajectory of the HVAC system, where the control trajectory is optimal in that it minimizes a cost function.

Controlling an HVAC system using an optimal setpoint schedule during a demand-response event

Controlling an HVAC system in association with a demand-response event

In controlling the HVAC system, a need to determine an expected indoor temperature profile for a particular schedule of setpoint temperatures may arise. To make such a determination, a thermodynamic model of the structure is used. The thermodynamic model is generated by fitting weighting factors of a set of basis functions to a variety of historical data including time information, temperature information, and HVAC actuation state information. The set of basis functions characterize an indoor temperature trajectory of the structure in response to a change in HVAC actuation state, and include an inertial carryover component that characterizes a carryover of a rate of indoor temperature change that was occurring immediately prior to the change in actuation state.

Generating and implementing thermodynamic models of a structure

A thermostat may include one or more memory devices comprising a stored setpoint schedule, one or more temperature sensors configured to provide temperature sensor measurements, and a processing system configured to be in operative communication the one or more memory devices to determine a setpoint temperature, and in still further operative communication with a heating, ventilation, and air conditioning (HVAC) system to control the HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication that a total instantaneous energy usage rate for a structure in which the thermostat is installed is projected to exceed a threshold amount; and altering the stored setpoint schedule to reduce an energy usage rate of the HVAC system.

Architecture for thermostat control during peak intervals

A thermostat my include a stored setpoint schedule, temperature sensors providing temperature sensor measurements; and a processing system configured to control an HVAC system based at least in part on the setpoint temperature and the temperature sensor measurements. The processing system may be configured to control the HVAC system by receiving an indication of a first time interval, where energy is available to the HVAC system at a first rate during the first time interval, energy is available to the HVAC system at a second rate during a second time interval that is outside of the first time interval, and the first rate is higher than the second rate; identifying a first one or more setpoints in the plurality of setpoints of the stored setpoint schedule that occur in the first time interval; and decreasing a temperature component of at least one of the first one or more setpoints.

Architecture for thermostat control during time-of-use intervals

Hazard detection systems and methods according to embodiments described herein are operative to enable a user to interface with the hazard detection system by performing a touchless gesture. The touchless gesture can be performed in a vicinity of the hazard detection system without requiring physical access to the hazard detection system. This enables the user to interact with the hazard detection system even if it is out of reach. The hazard detection system can detect gestures and perform an appropriate action responsive to the detected gesture. In one embodiment, the hazard detection system can silence its audible alarm or pre-emptively turn off its audible alarm in response to a detected gesture. Gestures can be detected by processing sensor data to determine whether periodic shapes are detected.

Systems and methods for detecting gesture events in a smart home system

A thermostat may be programmed to operate during cold-weather months by operating in a heat mode where the thermostat periodically causes the HVAC system to activate a heating function to heat an enclosure based at least in part on the stored setpoint schedule; receiving an indication from a thermostat management server of a demand response event while the thermostat is operating in the heat mode; determining whether the thermostat stores a user setting indicating that the thermostat should preheat the enclosure prior to reaching a scheduled setpoint in the stored setpoint schedule; and preheating the enclosure prior to the demand response event based on a determination that the thermostat stores the user setting indicating that the thermostat should preheat the enclosure prior to reaching the scheduled setpoint in the stored setpoint schedule.

Thermostat algorithms and architecture for efficient operation at low temperatures

In an embodiment, an electronic device may include storage containing processor-executable instructions and a current setpoint schedule, and a processor configured to execute the instructions. The instructions may cause the processor to control an environmental control system based at least in part on the current setpoint schedule, and to determine the current setpoint schedule by detecting user behavior that indicates satisfaction with setpoints, based at least in part on the detected user behavior, determining a preference function that maps weights indicating user preferences for setpoints, determining candidate setpoint schedules, scoring the candidate setpoint schedules against the weights of the preference function to obtain first scores, where candidate setpoint schedules that best fit the weights of the preference function have the highest first scores, modifying the first scores to obtain second scores, and selecting the candidate setpoint schedule with the highest second score as a new current setpoint schedule.

Enhanced automated environmental control system scheduling using a preference function

Thermostats disclosed herein are operable to control an HVAC system. In controlling the HVAC system, a need to determine an expected indoor temperature profile for a particular schedule of setpoint temperatures may arise. To make such a determination, a thermodynamic model of the structure is used. The thermodynamic model may be generated by fitting weighting factors of a set of basis functions to a variety of historical data including time information, temperature information, and HVAC actuation state information. The set of basis functions characterize an indoor temperature trajectory of the structure in response to a change in HVAC actuation state, and include an inertial carryover component that characterizes a carryover of a rate of indoor temperature change that was occurring immediately prior to the change in actuation state.

Systems and methods for detecting gesture events in a hazard detection system

Techniques for determining and using a thermodynamic model that characterizes a thermodynamic response of an enclosure conditioned by an HVAC system are disclosed. To determine a thermodynamic model, temperature information when the HVAC system operates in a first state may first be received. A response interval may then be determined where the response interval indicates an estimated time between when the HVAC system begins operating in the first state and when the temperature within the enclosure begins to change in a direction associated with the first state. Weighting factors corresponding to basis functions may then be determined, where the weighted basis functions characterize the temperature trajectory of the enclosure in response to the HVAC system operating in the first state. The basis functions may include a first basis function that is evaluated from a time that the HVAC system begins operating in the first state until a time when the response interval ends, and a second basis function that is evaluated beginning at the time when the response interval ends.

Thermodynamic model generation and implementation using observed HVAC and/or enclosure characteristics

Apparatus, systems, methods, and related computer program products for carrying out a demand response (DR) event via an intelligent, network-connected thermostat associated with a structure. The systems disclosed include an energy management system in operation with an intelligent, network-connected thermostat located at a structure. The thermostat is operable to control an HVAC system. Control during a DR event period may be performed based on an optimal control trajectory of the HVAC system, where the control trajectory is optimal in that it minimizes a cost function comprising a combination of a first factor representative of a total energy consumption during the DR event period, a second factor representative of a metric of occupant discomfort, and a third factor representative of deviations of a rate of energy consumption over the DR event period.

Controlling an HVAC system in association with a demand-response event with an intelligent network-connected thermostat

In an embodiment, an electronic device may include storage containing processor-executable instructions, a preference function that maps weights indicating likely user preferences for the range of values of a device setting in relation to a range of values of a variable, and a current automated device control schedule configured to control the device setting of the electronic device in relation to the variable, and a processor. The instructions may cause the processor to determine the current automated device control schedule based on the preference function by detecting user behavior that indicates satisfaction or dissatisfaction with values of the device setting in relation to the variable, updating the preference function based on the detected user behavior, and determining the current automated device control schedule by comparing a number of candidate device control schedules against the weights of the preference function and selecting the candidate with the highest score.

Growing community of inventors

San Mateo, CA, United States of America

Allen Joseph Minich