In the solution put forth, there is a frame structure (122) and an inner surface structure (124) in an installation frame (110) of an exhaust blower (108) of a building (100). A bottom part (130) of the frame structure is intended to be installed towards a lead-through (106) of the building, and a top part (132) towards the exhaust blower installed over it. The frame structure surrounds the inner surface structure so that it does not cover bottom and top parts (126, 128) of the inner surface structure. The inner surface structure forms a suction channel (134) allowing exhaust air (114) flow through the frame. Inside the installation frame, a controller (112) has been installed, adapted to measure the exhaust air flowing in the suction channel and to generate, on the basis of the measurement, a control command for the exhaust blower to control the operation of the exhaust blower.

In the solution put forth, there is a frame structure (122) and an inner surface structure (124) in an installation frame (110) of an exhaust blower (108) of a building (100). A bottom part (130) of the frame structure is intended to be installed towards a lead-through (106) of the building, and a top part (132) towards the exhaust blower installed over it. The frame structure surrounds the inner surface structure so that it does not cover bottom and top parts (126, 128) of the inner surface structure. The inner surface structure forms a suction channel (134) allowing exhaust air (114) flow through the frame. Inside the installation frame, a controller (112) has been installed, adapted to measure the exhaust air flowing in the suction channel and to generate, on the basis of the measurement, a control command for the exhaust blower to control the operation of the exhaust blower.

The present application provides a scenario temperature planning method and apparatus, a computer device, and a medium, where the scenario temperature planning method includes: obtaining original data in a current temperature planning cycle in a target scenario, where the original data is data generated based on a user's temperature adjustment operation; performing data merging and data elimination processing on the original data to obtain valid data; and adjusting temperature planning data of the current temperature planning cycle based on the valid data to obtain temperature planning data of a next temperature planning cycle of the current temperature planning cycle, so as to adjust a temperature in a target scenario in the next temperature planning cycle. The technical solution enables the adjusted temperature to meet the user's temperature requirements without requiring the user to manually plan and set the temperature, thereby improving user experience.

A method includes obtaining an optimized setpoint schedule for a time period, identifying a pre-cooling or pre-heating segment of the time period of the optimized setpoint schedule, adjusting the optimized setpoint schedule based on a characteristic of the pre-cooling or pre-heating segment to obtain an adjusted setpoint schedule, and operating the building equipment in accordance with the adjusted setpoint schedule.

A method includes obtaining an optimized setpoint schedule for a time period, identifying a pre-cooling or pre-heating segment of the time period of the optimized setpoint schedule, adjusting the optimized setpoint schedule based on a characteristic of the pre-cooling or pre-heating segment to obtain an adjusted setpoint schedule, and operating the building equipment in accordance with the adjusted setpoint schedule.

An information processing apparatus incudes a schedule determination unit configured to determine a schedule of an operating status for causing a temperature of an air-conditioned space of each of a plurality of load-side units to reach a specified set temperature at a specified set time, based on a learning model representing an input-output relationship between input data indicating an influencing factor of a thermal load of each of the load-side units and output data indicating the thermal load.

An information processing apparatus incudes a schedule determination unit configured to determine a schedule of an operating status for causing a temperature of an air-conditioned space of each of a plurality of load-side units to reach a specified set temperature at a specified set time, based on a learning model representing an input-output relationship between input data indicating an influencing factor of a thermal load of each of the load-side units and output data indicating the thermal load.

An air-conditioning apparatus having a refrigerant circuit, in which a compressor, an outdoor heat exchanger, an expansion device, and an indoor heat exchanger are connected by a pipe and refrigerant circulates in the pipe, includes an indoor fan configured to supply an indoor air to the indoor heat exchanger, and a controller configured to control the compressor and the indoor fan. The controller is configured to run the compressor at a start of a cooling operation, start running the indoor fan at less than a set minimum wind velocity after a first set time has elapsed since the compressor started operating, run the indoor fan at the set minimum wind velocity after a second set time has elapsed since the indoor fan started operating at less than the set minimum wind velocity, and run the indoor fan at a set wind velocity after a third set time has elapsed since the indoor fan started operating at the set minimum wind velocity.

Systems and methods are configured to control operation of an HVAC system providing climate control for a zone of a structure. In various embodiments, a constrained optimization problem is performed to set control commands for controlling operation of the HVAC system to achieve one or more objectives while providing a supply air flow at an air temperature and a humidity ratio for the zone at a future time. For instance, the optimization problem may include a cost function having constraints based on a desired temperature setpoint and a humidity ratio for the zone. A value is set for each control command based on the performance of the constrained optimization problem to achieve at least one of the objectives and as a result, the supply air flow at the air temperature and humidity ratio is provided by the HVAC system at the future time to the zone based on the values.

Systems and methods are configured to control operation of an HVAC system providing climate control for a zone of a structure. In various embodiments, a constrained optimization problem is performed to set control commands for controlling operation of the HVAC system to achieve one or more objectives while providing a supply air flow at an air temperature and a humidity ratio for the zone at a future time. For instance, the optimization problem may include a cost function having constraints based on a desired temperature setpoint and a humidity ratio for the zone. A value is set for each control command based on the performance of the constrained optimization problem to achieve at least one of the objectives and as a result, the supply air flow at the air temperature and humidity ratio is provided by the HVAC system at the future time to the zone based on the values.