In an air conditioner that uses a refrigerant mixture containing at least 1,2-difluoroethylene, high efficiency is achieved. In the air conditioner (1), a compressor (100, 200) can be driven without interposing a power conversion device between an AC power source (90, 190) and a motor (70, 170). Thus, it is possible to provide the air conditioner (1) that is environmentally friendly and has a relatively inexpensive configuration.

An automated method for managing weather related energy usage in a physical structure having and address using preexisting smart meters, preexisting weather stations and preexisting energy portals and with a dynamic energy model connected to a network.

The invention involves the automated testing of HVAC units using an energy management system. The automated HVAC test is performed to understand if one or more HVAC units are operational across one or more locations. If an HVAC unit is not operational, HVAC testing could be performed to understand which component or stage of the HVAC unit is not working as designed. The automated HVAC test is also used to calculate the efficiency of the HVAC unit(s) being tested. The various HVAC tests are performed on all HVAC units as a form of preventative maintenance and diagnostics. These tests can be scheduled on-demand, for a future date and time, or on a recurring schedule (monthly or quarterly). A report is generated for each HVAC test and can be viewed and exported from a cloud-based energy management platform.

The invention involves the automated testing of HVAC units using an energy management system. The automated HVAC test is performed to understand if one or more HVAC units are operational across one or more locations. If an HVAC unit is not operational, HVAC testing could be performed to understand which component or stage of the HVAC unit is not working as designed. The automated HVAC test is also used to calculate the efficiency of the HVAC unit(s) being tested. The various HVAC tests are performed on all HVAC units as a form of preventative maintenance and diagnostics. These tests can be scheduled on-demand, for a future date and time, or on a recurring schedule (monthly or quarterly). A report is generated for each HVAC test and can be viewed and exported from a cloud-based energy management platform.

A building cooling system includes one or more cooling devices operable to affect an indoor air temperature of a building and a system management circuit. The system management circuit is configured to obtain an objective function that includes a power consumption term and a comfort term, perform an optimization of the objective function over a time horizon to determine values of the cooling capacity of the cooling devices where each value of the cooling capacity corresponds to a time step of the time horizon, and control the cooling devices based on the values of the cooling capacity of the cooling devices. The comfort term of the objective function a difference between a prediction of the indoor air temperature of the building and a temperature setpoint for the building, while the power consumption term is a function of the power consumption of the one or more cooling devices.

A building cooling system includes one or more cooling devices operable to affect an indoor air temperature of a building and a system management circuit. The system management circuit is configured to obtain an objective function that includes a power consumption term and a comfort term, perform an optimization of the objective function over a time horizon to determine values of the cooling capacity of the cooling devices where each value of the cooling capacity corresponds to a time step of the time horizon, and control the cooling devices based on the values of the cooling capacity of the cooling devices. The comfort term of the objective function a difference between a prediction of the indoor air temperature of the building and a temperature setpoint for the building, while the power consumption term is a function of the power consumption of the one or more cooling devices.

A method of HVAC system performance monitoring using a computing device connected to at least one thermostat of an HVAC system in a building includes receiving thermostat data from the thermostat, the thermostat data including temperature setpoint data, measured building temperature data, and HVAC operation data for a time period. Weather data is received from a weather service for the time period, and the thermostat data is synchronized with the weather data with respect to time. At least one machine learning model is trained using the synchronized thermostat and weather data, and performance of the HVAC system over time is monitored using the trained machine learning model.

An HVAC control system having a cloud-based optimization engine in communication with a local building hub that interfaces with the building HVAC system and room units. The cloud-based optimization engine implements an optimal and predictive control strategy to integrate occupancy prediction, weather forecasting, and modeling of indoor infection risk, indoor air quality, and building energy consumptions. The control strategy includes a model-based predictive control and a model-free reinforcement learning approach. The control strategy considers outdoor weather (both thermal and air quality) conditions, indoor occupancy and requirements for IAQ and infectious risk reduction to decide whether outdoor air should be introduced and how much fresh air will be introduced into the space. Communications with the building hub allow the local HVAC unit to be driven according to the optimization plan. Individual room sensing units can provide local sensor data to the cloud-based optimization engine.

An HVAC control system having a cloud-based optimization engine in communication with a local building hub that interfaces with the building HVAC system and room units. The cloud-based optimization engine implements an optimal and predictive control strategy to integrate occupancy prediction, weather forecasting, and modeling of indoor infection risk, indoor air quality, and building energy consumptions. The control strategy includes a model-based predictive control and a model-free reinforcement learning approach. The control strategy considers outdoor weather (both thermal and air quality) conditions, indoor occupancy and requirements for IAQ and infectious risk reduction to decide whether outdoor air should be introduced and how much fresh air will be introduced into the space. Communications with the building hub allow the local HVAC unit to be driven according to the optimization plan. Individual room sensing units can provide local sensor data to the cloud-based optimization engine.

Disclosed is an air conditioner. The air conditioner includes: an outdoor unit having therein a compressor for compressing refrigerant; at least one indoor unit; a storage configured to store a database on a power quantity used by the air conditioner; and a controller. The controller is configured to: based on the database, calculate an estimated power quantity expected to be used by the air conditioner for at least a part of an entire period, based on a preset maximum power quantity for the entire period and the calculated estimated power quantity, determine a target power quantity for a specific unit time, which is expected to be used by the air conditioner for the specific unit time of the entire period; control the compressor for the specific unit time based on the target power quantity; and in response to arrival of a point in time to update the target power quantity, add, to the database, the power quantity used by the air conditioner for the specific unit time.