An HVAC system for automatically adjusting setpoint boundaries of a space includes building equipment configured to provide heating or cooling to the space to affect an environmental condition of the space and a controller. The controller obtains occupant setpoint adjustment data indicating occupant setpoint increases or occupant setpoint decreases at multiple times during a time interval and partitions the occupant setpoint adjustment data into time period bins based on the multiple times associated with the occupant setpoint adjustment data, each of the time period bins containing occupant setpoint adjustment data characterized by a common time attribute. The controller determines a number of occupant setpoint increases and a number of occupant setpoint decreases indicated by the occupant setpoint adjustment data within each time period bin and adjusts a setpoint boundary of the space based on the number of occupant setpoint increases or the number of occupant setpoint decreases.

An air conditioning system includes: an air conditioner that includes an outdoor unit including an outside air temperature sensor and an indoor unit including an indoor unit controller to control air conditioning operation and communicable with the outdoor unit; and a remote controller communicable with the indoor unit. The remote controller includes: a schedule storage to store information on an operation schedule of the air conditioner for each date and time, a reference temperature for determining an operation mode of the air conditioner, and an outside air temperature correction value; and an operation mode determiner to select the operation mode from among cooling, blowing, and heating using the information on the operation schedule, a corrected outside air temperature, and the reference temperature. The indoor unit controller controls the air conditioning operation using the reference temperature as a target temperature in the operation mode determined by the operation mode determiner.

The invention comprises systems and methods for evaluating changes in the operational efficiency of an HVAC system over time. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system, and status of said HVAC system. One or more processors receives measurements of outside temperatures from at least one source other than said HVAC system and compares said temperature measurements from said first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements.

Techniques are described for providing remote device (e.g., thermostat, lighting, appliance, etc.) control and/or energy monitoring. A system monitors sensor data captured by one or more sensors that sense attributes relevant to user presence at one or more monitored properties and status of one or more energy consuming devices associated with the one or more monitored properties. The system analyzes the monitored sensor data and the monitored device status with respect to a set of one or more rules and performs an operation related to controlling the one or more energy consuming devices based on the analysis of the monitored sensor data and the monitored device status with respect to the set of one or more rules.

Systems and methods for orchestrating the operation of energy-consuming loads, so as to minimize power consumption, are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or COP. In certain aspects, a COP uses specifically programmed application programming interfaces, or APIs, to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud-based control platform, through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud-based control platforms. By these and other means, the operation of a variety of energy-consuming loads can be more easily and efficiently orchestrated.

A finite-state machine control system including a cloud control platform, a state machine executor module, an intelligent control system (ICS) and air-conditioning equipment is disclosed. The cloud control platform receives a state-machine definition text-file written by and uploaded from a user terminal. The state-machine executor module transforms a description content of the state-machine definition text-file into mechanical execution codes which is compatible with the air-conditioning equipment, and executes the mechanical execution codes for creating a finite state-machine. The ICS controls the air-conditioning equipment according to the created finite state-machine. The present invention allows a finite-state machine of air-conditioning equipment to be created via the state machine definition text-file written by the user or generated automatically via computer programs and algorithms, thus the user doesn't need to have the ability of writing the machine execution codes.

A facility implementing systems and/or methods for achieving energy consumption/production and cost goals is described. The facility identifies various components of an energy system and assesses the environment in which those components operate. Based on the identified components and assessments, the facility generates a model to simulate different series/schedules of adjustments to the system and how those adjustments will effect energy consumption or production. Using the model, and based on identified patterns, preferences, and forecasted weather conditions, the facility can identify an optimal series or schedule of adjustments to achieve the user's goals and provide the schedule to the system for implementation. The model may be constructed using a time-series of energy consumption and thermostat states to estimate parameters and algorithms of the system. Using the model, the facility can simulate the behavior of the system and, by changing simulated inputs and measuring simulated output, optimize use of the system.

The invention comprises systems and methods for evaluating changes in the operational efficiency of an HVAC system over time. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system, and status of said HVAC system. One or more processors receives measurements of outside temperatures from at least one source other than said HVAC system and compares said temperature measurements from said first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements.

Computer-implemented systems and methods for estimating a replacement status of an HVAC air filter. Outdoor weather data (e.g., outdoor temperature information), is obtained. A Total Runtime Value of the HVAC system is determined based upon the obtained outdoor weather data. Finally, a replacement status of the air filter is estimated as a function of a comparison of the Total Runtime Value with a Baseline Value. By correlating air filter replacement status with an estimated runtime of the HVAC system, a credible predictor of air filter usage is provided. By estimating fan runtime based on easily-obtained outdoor weather data, the methods are readily implemented with any existing HVAC system and do not require installation of sensors or other mechanical or electrical components to the HVAC system.

In some implementations, a system performs proactive performance tests for an appliance before a time for an operational change in usage of the appliance. Usage data for an appliance associated with a property may be obtained. The obtained usage data indicates past activity of the appliance and present operational status of the appliance. Weather forecast data associated with a location of the property can be obtained. A time for an operational change in usage of the appliance can be predicted based at least on the obtained usage data for the appliance and the obtained weather forecast data. An operation directed to conducting one or more performance tests on the appliance can be performed before the predicted time for the operational change in usage of the appliance. One or more communications related to the one or more performance tests of the appliance can be provided to a client device.