Disclosed herein is an indoor unit including: a load detector for detecting a heavy-load area to bear a relatively heavy air-conditioning load during a heating mode of operation and a light-load area to bear a lighter air-conditioning load than the heavy-load area from a perimeter zone of a space to be air-conditioned; and an air volume adjuster for setting the volume of air blown toward the light-load area to be lower than that of air blown toward the heavy-load area in a horizontal blowing mode. This allows the entire room, including the perimeter zone, to be air-conditioned efficiently during the heating mode of operation with temperature non-uniformity reduced in the room.

A refrigeration system includes at least one compressor, a condenser, one or more sensors, and a controller. The one or more sensors are operable to sense data associated with the refrigeration system. The controller is operable to receive operating data associated a first control variable and a second control variable, the operating data received from the one or more sensors. The controller is further operable to determine, based on the operating data, that a control objective is not met, and operate the refrigeration system according to a configuration selected to cause the control objective to be met in response to determining that the control objective is not being met, wherein operating the refrigeration system according to the configuration selected to cause the control objective to be met comprises overriding control of the second control variable until the control objective is met.

A heating, ventilation, and air conditioning (HVAC) control device configured to generate the machine learning model using the first set of weights and the second set of weights. The machine learning model is configured to output a probability that a user is present at the space based on an input that identifies a day of the week and a time of a day. The device is further configured to determine a probability that a user is present at the space for a predicted occupancy schedule using the machine learning model, to determine an occupancy status based on a determined probability that a user is present at the space, and to set a predicted occupancy status in the predicted occupancy schedule based on a determined occupancy status for each time entry. The device is further configured to output the predicted occupancy schedule.

A thermostat of an HVAC system receives active event parameters from a utility provider. The active event parameters include a start time, a stop time, and a predefined temperature setpoint for the active event, which is associated with a requirement to decrease energy consumption between the start time and the stop time. Following the start time, the thermostat adjusts a setpoint temperature of the HVAC system to the predefined setpoint temperature. After adjusting the setpoint temperature to the predefined setpoint temperature, a new user setting for operation of the HVAC system is received. The thermostat determines that energy consumed during operation of the HVAC system according to the new user setting is less than or equal to energy consumed during operation of the HVAC system according to the predefined setpoint temperature. Following this determination, the thermostat causes the HVAC system to operate according to the new user settings.

A system and method for controlling a system that includes a variable speed compressor are described. The method can provide improved accuracy in the control of a system, for example, a heating, ventilating, and air condition (HVAC) system that includes a variable speed compressor, and can reduce a compressor cycling frequency of the compressor when a required capacity is below a minimum capacity of the compressor.

A first comparison-period specifier specifies a first to-be-compared period in a pre-implementation period before implementation of an energy saving control. A second comparison-period specifier specifies as a second to-be-compared period a to-be-compared candidate period having the highest similarity level between: parameters in a first parameter comparison period including a first comparison period and a first period immediately before or after the first comparison period, and parameters in a second parameter comparison period including a to-be-compared candidate period and a second period immediately before or after the to-be-compared candidate period. An energy saving diagnoser diagnoses the level of energy saving derived from the implementation of an energy saving control based on a power consumption amount in the first to-be-compared period and a power consumption amount in the second to-be-compared period.

The invention comprises a system for calculating a value for the effective thermal mass of a building. The climate control system obtains temperature measurements from at least a first location conditioned by the climate system. One or more processors receive measurements of outside temperatures from at least one source other than the control system and compare the temperature measurements from the first location with expected temperature measurements. The expected temperature measurements are based at least in part upon past temperature measurements obtained by said HVAC control system and said outside temperature measurements. The processors then calculate one or more rates of change in temperature at said first location.

An equipment management system includes an information processing apparatus obtains equipment information about equipment, and a management apparatus. The management apparatus communicates the equipment information with the information processing apparatus under a predetermined communication condition, and manages the equipment. Either or both of the management apparatus and the information processing apparatus include a candidate communication condition generating unit that generates one or more candidate communication conditions in accordance with one or both of a state of the equipment and a state of an installation space in which the equipment is installed.

A controller for heating, ventilation, or air conditioning (HVAC) equipment includes a communications interface configured to communicate with first HVAC equipment and second HVAC equipment and a processing circuit communicably coupled to the communications interface. The processing circuit is configured to detect a staging event for the first HVAC equipment occurring at a first time, obtain a delay time based on an estimated amount of time required to reach steady state after the staging event for the first HVAC equipment occurs at the first time, determine whether the delay time has elapsed since the staging event for the first HVAC equipment has occurred, and prevent the second HVAC equipment from staging in response to a determination that the delay time has not elapsed since the staging event for the first HVAC equipment has occurred.

A method for determining the level of efficiency of a ventilation system of an electrical enclosure intended to house one or more electrical devices, the method including a learning step including a step for determining a profile of the power dissipated via the Joule effect by each electrical device, an evaluation step for evaluating the level of efficiency of the ventilation system, including a step for determining the average air flow rate of a fan from a profile of the temperature of the air outside the enclosure obtained over an evaluation period, a profile of the temperature of the air at the outlet of the enclosure, and the dissipated power profile determined during the learning step, a step for comparing the average air flow rate with one or more threshold values in order to determine the level of efficiency of the ventilation system.