A heating, ventilation, and air conditioning (HVAC) system may be zoned into one or more zone. The HVAC system may include HVAC components, sensors, and one or more register vents that may include vent dampers (e.g., electronically controllable vent dampers or manually operated vent dampers). Opening and closing of the vent dampers may facilitate creating zones or sub-zones in the HVAC system configuration. An HVAC control system may receive a request for conditioned air in one or more of the zones, determine a damper setting for at least one of the vent dampers, communicate the determined damper setting to a vent damper or user interface, determine which HVAC components should be active, if any, and/or provide controls signals to activate or keep active the HVAC components that are determined to be active.

A method for providing personalized comfort to occupants of an environmentally conditioned space includes sensing a pre-adjustment pressure within a variable air volume diffuser, remotely adjusting a position an individually-adjustable directional outlet of the variable air volume diffuser, sensing a post-adjustment pressure within the variable air volume diffuser, and modifying the airflow through the variable air volume diffuser such that the post-adjustment pressure is equal to the pre-adjustment pressure. The variable air volume diffuser includes individually-adjustable directional outlets and a controller configured to regulate air pressure within the variable air volume diffuser when an individually adjustable directional outlet is adjusted. A user device in operative communication with the variable air volume diffuser includes a user interface to remotely adjust an adjustable directional outlet of the variable air volume diffuser to provide personalized comfort for the user. In embodiments, the variable air volume diffuser responds to spoken commands.

An energy management system is configured to calculate a percentage of satisfied based on the report data for each of the plurality of buildings; create, for each of the plurality of buildings, a plan for operating each of the air-conditioning facilities based on the percentage of satisfied and a predetermined target percentage of satisfied; calculate a first energy consumption amount based on the first piece of data; calculate a second energy consumption amount based on the second piece of data, the third piece of data, and the fourth piece of data, the second energy consumption amount being obtained when the each of the air-conditioning facilities is operated after a lapse of a predetermined time period; and control, when the first energy consumption amount is larger than the second energy consumption amount, the operation of the each of the air-conditioning facilities so as to achieve the second energy consumption amount.

A wireless network system is incorporated in an air conditioning system. A user is accessible to the wireless network system for controlling the air conditioner. The wireless network system includes an AP (access point) equipment, an air conditioning controller and a user-operable terminal. The terminal and the air conditioning controller are connected communicably and wirelessly when a dedicated application is actuated in the terminal. AP information (such as a password) is transmitted from the terminal to the air conditioning controller to establish coordination (i.e., pairing) between the terminal and the air conditioning controller in a state where the terminal and the air conditioning controller are connected mutually and wirelessly. The AP information identifies the AP equipment. In this coordinated state, the access to the AP equipment is executed based on the AP information. Authentication is performed when the terminal and the air conditioning controller are mutually and directly connected.

A HVAC control system comprising a user interface adapted to receive comfort feedback from a user. A processor is adapted to receive the comfort feedback and input data corresponding to one or more comfort factors and respective values of the comfort factors. The processor is adapted to build a comfort model for the user based on the comfort feedback and the input data, with the comfort model correlating a comfort score to one or more values of one or more of the comfort factors. The processor is configured to adjust one or more functions of an HVAC unit to vary one or more comfort factors such that a predetermined comfort score is achieved. An associated method and an associated system are also provided.

This application discloses a comfort adjustment method and a related apparatus. The method includes: obtaining environment information and user information that correspond to a first space, where the first space is a non-open space; determining, based on the environment information, the user information, and a thermal comfort representation indicator, a control indicator of at least one device corresponding to the first space; and controlling the at least one device based on the control indicator of the at least one device.

Using processes and methods described herein, a digital twin of a physical space can train itself using sensors and other information available from the building. In some embodiments, a system to be controlled comprises a controller that is connected to sensors. This controller also has a thermodynamic model of the system to be controlled within memory associated with the controller. The thermodynamic model has neurons that represent distinct pieces of a controlled space, such as a piece of equipment or a thermodynamically coherent section of a building, such as a window. The neurons represent these distinct pieces of the controlled space using parameter values and equations that model physical behavior of state with reference to the distinct piece of the controlled state. A machine learning process refines the thermodynamic model by modifying the parameter values of the neurons, using sensor data gathered from the system to be controlled as ground truth to be matched by behavior of the thermodynamic model. The thermodynamic model may be warmed up by running the model using state data as input.