Techniques for performing an emissions demand response (EDR) event are described. In an example, a cloud-based HVAC control system may obtain a first emissions rate forecast and generate an EDR event with a start time and end time based on the first emissions rate forecast. The EDR event may then be transmitted to a thermostat and stored in a memory of the thermostat. At the start time, the thermostat may commence controlling an HVAC system according to the EDR event. After the start time and prior to the end time, the cloud-based HVAC control system may obtain a second emissions rate forecast and generate a modified EDR event with a modified end time. The modified EDR event may be transmitted to the thermostat before the end time and/or the modified end time whereupon the thermostat may control the HVAC system accordingly until the modified end time is reached.

The present disclosure provides an air conditioner and a control method thereof. The control method of the air conditioner is capable of acquiring a voice of a user including a state of the user, transmitting the voice of the user to an external server, receiving, from the external server, a control command acquired by using a cooling tendency of the user and the state of the user determined on the basis of a usage history of the air conditioner, and controlling the air conditioner on the basis of the control command. In particular, at least a part of a method of acquiring a control command on the basis of a cooling tendency of a user may use an artificial intelligence model trained according to at least one of machine learning, a neural network, and deep learning algorithms.

An environmental control system for a building space including heating, ventilation, or air conditioning (HVAC) equipment that operates to control a temperature of the building space. The system includes lighting equipment that operates to control a luminosity and affect a heat load disturbance for the building space. The system includes an environmental controller including a processing circuit configured to predict the heat load disturbance based on potential operating states of the lighting equipment over a time period. The heat load disturbance affects the temperature of the building space. The processing circuit is configured to generate control decisions for the HVAC and lighting equipment based on the predicted heat load disturbance and subject to constraints on the temperature and luminosity of the building space. The processing circuit is configured to operate the HVAC and lighting equipment based on the control decisions.

A cascaded control system for coordinating and controlling carbon emissions associated with operating building equipment distributed across a plurality of subsystems includes a first controller configured to generate carbon emissions targets for each of a plurality of subsystems using a predictive control process that accounts for an aggregate carbon emissions of the plurality of subsystems predicted to result from the carbon emissions targets. The cascaded control system also includes a plurality of second controllers, each corresponding to one of the plurality of subsystems and configured to generate control decisions for building equipment of the corresponding subsystem that are predicted to cause the building equipment to achieve the carbon emissions targets for the corresponding subsystem; and operate the building equipment of the corresponding subsystem using the control decisions.

The air conditioning system comprises: an air conditioner; an inference device to infer data representing a total amount of a power demand value exceeding a set value for a prediction target period from input data including at least one of operation data of the air conditioner for a period prior to the prediction target period, state data of a user of the air conditioner for the period prior to the prediction target period, weather prediction data for the prediction target period, or characteristic data of the room in which the air conditioner is installed; and a control device to cause the air conditioner to perform a heat storage operation depending on a predicted value of the total amount of the power demand value.

A method of operating an HVAC system using a controller includes predicting a first predicted temperature of an enclosed space during an unoccupied time with the HVAC system off. The controller determines if the first predicted temperature is less than a set-point temperature. Responsive to a determination that the first predicted temperature is less than the set-point temperature, the controller predicts a second predicted temperature of the enclosed space if the HVAC system is operated for a first runtime. The controller determines if the second predicted temperature is less than the set-point temperature and, responsive to a determination that the second predicted temperature is not less than the set-point temperature, the controller operates the HVAC system for the first runtime.

Techniques for providing an adaptive energy management system for responding to extreme weather conditions are described herein. In an embodiment, a server computer stores multiple policy datasets each representing HVAC control policy for different structure locations and one or more extreme weather conditions. The server computer receives weather condition data comprising a condition identifier of a then-current extreme weather condition in association with a location identifier specifying a particular geographical region. Based on the location identifier, a particular structure location, being within the particular geographic region, is identified. Based on the particular structure location, a particular policy dataset from among the policy datasets is identified. The particular policy dataset is transformed into HVAC equipment instructions, which the server computer transmits, over a network, to HVAC equipment at the particular structure location which, when executed, cause the HVAC equipment to execute an action in accordance with the particular policy dataset.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing thermal modeling. In one aspect, a method includes receiving monitoring data comprising temperature data measured inside a site, mode data, and state data, receiving weather data descriptive of weather at the site, and aligning the received temperature data, mode data, and state data with the received weather data. The method also includes determining an internal heat gain representing an amount of heat generated at the site irrespective of the heating or cooling system, determining at least one of a thermal product for the site or a thermal potential for the heating or cooling system, generating, based on the internal gain and the thermal product or the thermal potential, a thermal model for the site, and providing, as output, the generated thermal model.

A control system for controlling consumption of energy in an environment including a controller having a processor and a real time clock, the real time clock being configured to coordinate operations of the processor with timing of the designated peak period, the processor being configured to determine a minimum pre-operating period and to signal an air conditioning and/or space heating system to enter an operating state for at least the minimum pre-operating period before the designated peak period begins and enter a non-operating state after the designated peak period begins; an operating program having processing parameters and processing procedure for determining the minimum pre-operating period, wherein the processing parameters and processing procedure comprise determining the minimum pre-operating period using thermal mass of the environment, costs for the consumption of energy, and efficiency of the air conditioning and/or space heating system.

An air conditioning system control device 10 includes: a switching unit 11 that, when a parameter relating to the indoor environment in which the air conditioning system operates does not satisfy a first condition while the air conditioning system is operating in a first operation mode that is an operation mode in which setting values computed on the basis of a prediction model are used as the setting values for the air conditioning system, switches the operation mode of the air conditioning system to a second operation mode that is an operation mode in which the computed setting values are not used as the setting values for the air conditioning system.