Abstract: A facility providing systems and methods for managing and optimizing thermal comfort is provided. The facility is a software algorithm that intelligently detects the thermal comfort preferences of residential smart thermostat users, where a user's “comfort preference” is defined to refer to an estimate of a measurement of the user's comfort across varying values of some set of exogenous factors, including but not limited to indoor temperature, the time of day, the day of the week, and weather conditions. This facility encompasses the use of this “comfort preference” for the creation of an optimal schedule of setpoints for a residential thermostat which is configured to optimize some objective, including potentially user comfort, energy efficiency, load shift, or cost.

Abstract: A facility providing systems and methods for managing and optimizing thermal comfort is provided. The facility is a software algorithm that intelligently detects the thermal comfort preferences of residential smart thermostat users, where a user's “comfort preference” is defined to refer to an estimate of a measurement of the user's comfort across varying values of some set of exogenous factors, including but not limited to indoor temperature, the time of day, the day of the week, and weather conditions. This facility encompasses the use of this “comfort preference” for the creation of an optimal schedule of setpoints for a residential thermostat which is configured to optimize some objective, including potentially user comfort, energy efficiency, load shift, or cost.

Abstract: A facility providing systems and methods for managing and optimizing thermal comfort is provided. The facility is a software algorithm that intelligently detects the thermal comfort preferences of residential smart thermostat users, where a user's “comfort preference” is defined to refer to an estimate of a measurement of the user's comfort across varying values of some set of exogenous factors, including but not limited to indoor temperature, the time of day, the day of the week, and weather conditions. This facility encompasses the use of this “comfort preference” for the creation of an optimal schedule of setpoints for a residential thermostat which is configured to optimize some objective, including potentially user comfort, energy efficiency, load shift, or cost.

Abstract: A facility providing systems and methods for managing and optimizing thermal comfort is provided. The facility is a software algorithm that intelligently detects the thermal comfort preferences of residential smart thermostat users, where a user's “comfort preference” is defined to refer to an estimate of a measurement of the user's comfort across varying values of some set of exogenous factors, including but not limited to indoor temperature, the time of day, the day of the week, and weather conditions. This facility encompasses the use of this “comfort preference” for the creation of an optimal schedule of setpoints for a residential thermostat which is configured to optimize some objective, including potentially user comfort, energy efficiency, load shift, or cost.

Abstract: A facility providing systems and methods for managing and optimizing thermal comfort is provided. The facility is a software algorithm that intelligently detects the thermal comfort preferences of residential smart thermostat users, where a user's “comfort preference” is defined to refer to an estimate of a measurement of the user's comfort across varying values of some set of exogenous factors, including but not limited to indoor temperature, the time of day, the day of the week, and weather conditions. This facility encompasses the use of this “comfort preference” for the creation of an optimal schedule of setpoints for a residential thermostat which is configured to optimize some objective, including potentially user comfort, energy efficiency, load shift, or cost.