Techniques for instantiating energy saving setpoint adjustments are described. In an example, a heating, ventilation, and air conditioning (HVAC) system is controlled via a thermostat during a first time period according to a first temperature setpoint schedule including one or more temperature setpoints and a first usage amount of the HVAC system is monitored during the first time period. After it is determined that the first usage amount of the HVAC system during the first time period has met a first predefined HVAC runtime threshold criterion, a second temperature setpoint schedule is generated with at least one of the one or more temperature setpoints being adjusted to decrease energy usage by the HVAC system compared to the first temperature setpoint schedule. The HVAC system is then controlled via the thermostat during a second time period according to the second temperature setpoint schedule.

A building energy system includes HVAC equipment, green energy generation, a battery, and a predictive controller. The HVAC equipment provide heating or cooling for a building. The green energy generation collect green energy from a green energy source. The battery stores electric energy including at least a portion of the green energy provided by the green energy generation and grid energy purchased from an energy grid and discharges the stored electric energy for use in powering the HVAC equipment. The predictive controller generates a constraint that defines a total energy consumption of the HVAC equipment at each time step of an optimization period as a summation of multiple source-specific energy components and optimizes the predictive cost function subject to the constraint to determine values for each of the source-specific energy components at each time step of the optimization period.

A control system for a HVAC system for a structure and including a blower that flows air over an indoor heat exchanger. The control system may include a first input device, a first sensor, and a processor in electronic communication with the first input device, the first sensor, and the blower of the HVAC system. The first input device may be operable to accept a zoning mode selection. The first sensor may be sensor operable to measure a first temperature at a first location within the structure. The processor may be programmed to determine a cooling or heating demand on the HVAC system based on an input temperature and the first measured temperature. The processor may be further programmed to adjust an air flow rate produced by the blower based on the demand on the HVAC system and the zoning mode selection.

Systems and methods for operating a water recovery system and include activating a plurality of dampers, a fan, and a refrigeration system of the water recovery system. The method includes measuring an ambient air temperature of the water recovery system based on data obtained from an ambient air temperature sensor. The method includes measuring one or more evaporator temperatures associated with an evaporator of the water recovery system based on data obtained from one or more evaporator temperature sensors. The method includes determining an optimal evaporator air temperature of the water recovery system based on the one or more evaporator temperatures and the ambient air temperature. The method includes setting a speed of the fan of the water recovery system based on the optimal evaporator air temperature.

During an initial period of time, an HVAC controller stores a record of an energy demand of the HVAC system that corresponds to an amount of energy used to operate the HVAC system. For a future time period, an anticipated energy demand of the HVAC system is determined. The controller then recursively determines, for each of a plurality of time points within the future time period, an anticipated indoor humidity value using the anticipated energy demand and the record of the energy demand. The HVAC system is operated based at least in part on the anticipated indoor humidity value.

An air conditioning control system includes a plurality of remote control terminals and a server. The plurality of remote control terminals each calculates a time required for a user of the remote control terminal to return to a building from outside the building, and transmits information indicating the time required to the server. The server calculates an estimated time when a user who returns to the building first among the plurality of users returns to the building on the basis of the time required, and transmits a command for changing air conditioning setting to an air conditioner in stages from a time when the estimated time is calculated to the estimated time calculated.

A method of monitoring an air filter in a heating, ventilation, and air conditioning (HVAC) system that includes operating a blower motor at a desired torque; monitoring a horsepower of the blower motor over a selected time period when the blower motor is operating at the desired torque; determining a moving average of the horsepower of the blower motor over the selected time period; detecting when the moving average drops below an established baseline moving average by a selected percentage; and activating a notification to check or change the air filter of the HVAC system.

A system includes multiple HVAC systems. After receiving a demand request, a multiple-system controller a first anticipated power consumption associated with operating a first HVAC system at a first temperature setpoint during a future period of time of the demand response request and a second anticipated power consumption associated with operating a second HVAC system at a second temperature setpoint during the future period of time. Based at least in part on the first and the second anticipated power consumptions, a staging schedule is determined that indicates when to operate the first and second HVAC systems.

An integrated system and method measures building characteristics and user behavior to provide real-time and forecasted utility usages and costs. The system gathers current and historical heating and cooling load data, compares the data with current and historical weather data and a building system set point, and calculates the heating or cooling load needed for the building based on the user's call for heat or cooling and the ambient environmental conditions. The system additionally analyzes individual device usage using usage signatures and user inputted tracking to create a comprehensive real-time and forecast of utility usages with the estimated costs. Through history of selections with usage changes corresponding to user input of individual devices, the system will be able to learn various devices' usage. The system then creates a comprehensive, real-time forecast of utility costs including the foregoing characteristics.

This Patent application is based on a new method for calculating the hourly heating load for the heating elements of HVAC systems, with a potential for saving over 50% of the current fuel use by these systems. The method is based on using hourly outside air temperature from one or more thermometer installed along the vertical center of each of the building's orientations, and at the roof center. The temperature data, the building surface areas with different heat transmission characteristics in each orientation, plus hourly air infiltration rate into the building, adjusted for overall system efficiency, and Codes and regulatory requirements would yield the total hourly heating load. The fuel feed would then be automatically adjusted to release the hourly required fuel volume, or wattage, to the heating elements. The installed thermometer system could also be used to calculate the hourly cooling load for the building's air conditioning system, during the summer season.