Abstract: 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 setpoint schedule of the HVAC system. Candidate setpoint schedules may be simulated to identify an optimal schedule.

Abstract: 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.

Abstract: A method includes a system that operates according to a control schedule; detects events that indicate occupancy; stores a record of the events that indicate occupancy in one or more memory devices; and enters an auto-away state. A determination to enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected and the stored record of the events that indicate occupancy. The system may also detect a pattern of instances where the auto-away state is entered over a plurality of days and adjusts the control schedule based at least in part on the pattern of instances where the auto-away state is entered.

Abstract: A method includes a system that operates according to a control schedule; detects events that indicate occupancy; stores a record of the events that indicate occupancy in one or more memory devices; and enters an auto-away state. A determination to enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected and the stored record of the events that indicate occupancy. The system may also detect a pattern of instances where the auto-away state is entered over a plurality of days and adjusts the control schedule based at least in part on the pattern of instances where the auto-away state is entered.

Abstract: 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.

Abstract: The current application is directed to intelligent controllers that use sensor output and electronically stored information to determine whether or not one or more types of entities are present within an area, volume, or environment monitored by the intelligent controllers. The intelligent controllers select operational modes and/or modify control schedules with respect to the presence and absence of the one or more entities. The intelligent controllers selectively carry out scheduled control operations during periods of time when one or more types of entities are determined not to be in a controlled environment.

Abstract: 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.

Abstract: A method includes operating a controller according to a control schedule; detecting events that indicate occupancy; storing a record of the events that indicate occupancy in one or more memory devices; and causing the controller to enter an auto-away state. A determination that the controller should enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected; and the stored record of the events that indicate occupancy. The method also includes detecting a pattern of instances where the controller enters the auto-away state over a plurality of days; and adjusting the control schedule based at least in part on the pattern of instances where the controller enters the auto-away state.

Abstract: A method of using a server to update stored control schedules for environmental controllers includes communicating with an environmental controller that controls, during a monitoring period, an environmental system in an enclosure according to a stored control schedule; receiving a first immediate-control input provided through the environmental controller during the monitoring period; receiving a first control-schedule change provided through the environmental controller during the monitoring period; receiving a second immediate-control input provided through a user device during the monitoring period; receiving a second control-schedule change provided through the user device during the monitoring period; processing at least the first immediate-control input, the first control-schedule change, the second immediate-control input, and the second control-schedule change together to generate an updated control schedule; and causing the environmental controller to control the environmental system according to th

Abstract: The current application is directed to intelligent controllers that continuously, periodically, or intermittently calculate and display the time remaining until a control task is projected to be completed by the intelligent controller. In general, the intelligent controller employs multiple different models for the time behavior of one or more parameters or characteristics within a region or volume affected by one or more devices, systems, or other entities controlled by the intelligent controller. The intelligent controller collects data, over time, from which the models are constructed and uses the models to predict the time remaining until one or more characteristics or parameters of the region or volume reaches one or more specified values as a result of intelligent controller control of one or more devices, systems, or other entities.

Abstract: Systems and methods are provided for efficiently controlling energy-consuming systems, such as heating, ventilation, or air conditioning (HVAC) systems. For example, an electronic device used to control an HVAC system may encourage a user to select energy-efficient temperature setpoints. Based on the selected temperature setpoints, the electronic device may generate or modify a schedule of temperature setpoints to control the HVAC system.

Abstract: The current application is directed to intelligent controllers that initially aggressively learn, and then continue, in a steady-state mode, to monitor, learn, and modify one or more control schedules that specify a desired operational behavior of a device, machine, system, or organization controlled by the intelligent controller. An intelligent controller generally acquires one or more initial control schedules through schedule-creation and schedule-modification interfaces or by accessing a default control schedule stored locally or remotely in a memory or mass-storage device. The intelligent controller then proceeds to learn, over time, a desired operational behavior for the device, machine, system, or organization controlled by the intelligent controller based on immediate-control inputs, schedule-modification inputs, and previous and current control schedules, encoding the desired operational behavior in one or more control schedules and/or sub-schedules.

Abstract: A method includes operating a controller according to a control schedule; detecting events that indicate occupancy; storing a record of the events that indicate occupancy in one or more memory devices; and causing the controller to enter an auto-away state. A determination that the controller should enter the auto-away state may be based at least in part on a length of a time interval during which no events that indicate occupancy were detected; and the stored record of the events that indicate occupancy. The method also includes detecting a pattern of instances where the controller enters the auto-away state over a plurality of days; and adjusting the control schedule based at least in part on the pattern of instances where the controller enters the auto-away state.

Abstract: HVAC schedules may be programmed for a thermostat using a combination of pre-existing schedules or templates and automated schedule learning. For example, a pre-existing schedule may be initiated on the thermostat and the automated schedule learning may be used to update the pre-existing schedule based on users' interactions with the thermostat. The preexisting HVAC schedules may be stored on a device or received from a social networking service or another online service that includes shared HVAC schedules.

Abstract: The current application is directed to intelligent controllers that initially aggressively learn, and then continue, in a steady-state mode, to monitor, learn, and modify one or more control schedules that specify a desired operational behavior of a device, machine, system, or organization controlled by the intelligent controller. An intelligent controller generally acquires one or more initial control schedules through schedule-creation and schedule-modification interfaces or by accessing a default control schedule stored locally or remotely in a memory or mass-storage device. The intelligent controller then proceeds to learn, over time, a desired operational behavior for the device, machine, system, or organization controlled by the intelligent controller based on immediate-control inputs, schedule-modification inputs, and previous and current control schedules, encoding the desired operational behavior in one or more control schedules and/or sub-schedules.

Abstract: Various arrangements for installing or configuring an electronic device are presented. The device may determine which wire connectors of a set of one or more wire connectors have a wire attached. A user inquiry may be output based on the electronic device identifying the wire connector with which the wire has been connected. The electronic device may be operated based on the response to the user inquiry and the electronic device identifying the wire connector with which the wire has been connected.

Abstract: A control system includes an energy management system in operation with intelligent, network-connected thermostats located in structures. The thermostats are operable to control HVAC systems. 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.

Abstract: A thermostat may include a memory and a processing system. The processing system may operate by determining a set of wake-up conditions for the processor to enter into a second operating state from a first operating state, the set of wake-up conditions including at least one threshold value associated with at least one environmental and/or time-of-day condition; causing the set of wake-up conditions to be stored in a memory; operating in a first mode in which the processor is in the first operating state during a time interval subsequent to causing the set of wake-up conditions to be stored in the memory; determining, while the processor is in the first operating state, whether at least one of the set of wake-up conditions has been met; and then operating in a second mode in which the processor is in the second operating state.

Abstract: 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.

Abstract: Various arrangements for installing or configuring an electronic device are presented. The device may determine which wire connectors of a set of one or more wire connectors have a wire attached. A user inquiry may be output based on the electronic device identifying the wire connector with which the wire has been connected. The electronic device may be operated based on the response to the user inquiry and the electronic device identifying the wire connector with which the wire has been connected.