Building hvac system with multi-objective optimization control

US2024176319A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2024176319-A1
Application numberUS-202418432947-A
CountryUS
Kind codeA1
Filing dateFeb 5, 2024
Priority dateJul 12, 2019
Publication dateMay 30, 2024
Grant date

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  1. Title

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  2. Abstract

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  5. First independent claim

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  7. Citations and related patents

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Abstract

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A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building is configured to obtain predictive models that predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment. The controller executes a multi-objective optimization process using the predictive models to produce multiple sets of optimization results corresponding to different values of the control decision variables, the energy control objective, and the air quality control objective. The controller selects one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective. The controller operates the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

First claim

Opening claim text (preview).

What is claimed is: 1 . A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building, the controller comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining one or more predictive models configured to predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment; executing a multi-objective optimization process using the one or more predictive models to produce multiple sets of optimization results corresponding to different values of the control decision variables, the energy control objective, and the air quality control objective; selecting one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective; and operating the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results. 2 . The controller of claim 1 , wherein the energy control objective comprises an amount of energy consumption predicted to result from operating the HVAC equipment in accordance with the control decision variables. 3 . The controller of claim 1 , wherein the energy control objective comprises an amount of carbon emissions predicted to result from operating the HVAC equipment in accordance with the control decision variables. 4 . The controller of claim 1 , wherein the energy control objective comprises a cost of energy consumed by the HVAC equipment predicted to result from operating the HVAC equipment in accordance with the control decision variables. 5 . The controller of claim 1 , wherein the air quality control objective comprises an infection risk predicted to result from operating the HVAC equipment in accordance with the control decision variables. 6 . The controller of claim 1 , wherein the air quality control objective comprises an amount or concentration of particles in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables. 7 . The controller of claim 1 , wherein the air quality control objective comprises an indoor air quality score predicted to result from operating the HVAC equipment in accordance with the control decision variables. 8 . The controller of claim 1 , wherein the air quality control objective comprises an amount or concentration of carbon dioxide in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables. 9 . The controller of claim 1 , wherein the air quality control objective comprises one or more comfort parameters affecting occupant comfort in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables. 10 . The controller of claim 1 , wherein executing the multi-objective optimization process comprises executing multiple optimization processes using different sets of constraints for the control decision variables or different search spaces for the control decision variables, the multiple optimization processes producing corresponding sets of the multiple sets of optimization results. 11 . The controller of claim 1 , wherein executing the multi-objective optimization process comprises optimizing an objective function that quantifies the values of the energy control objective subject to a constraint based on the values of the air quality control objective. 12 . The controller of claim 1 , wherein: executing the multi-objective optimization process comprises performing an optimization of an objective function comprising either (i) the energy control objective without the air quality control objective or (ii) the air quality control objective without the energy control objective; the optimization of the objective function is performed subject to a constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function; and the multiple sets of optimization results are produced by adjusting the constraint on whichever of the energy control objective or the air quality control objective is not included in the objective function and repeating the optimization of the objective function for multiple different values of the constraint. 13 . The controller of claim 1 , wherein executing the multi-objective optimization process comprises optimizing an objective function subject to one or more constraints comprising the one or more predictive models. 14 . The controller of claim 1 , wherein selecting one or more of the sets of optimization results comprises selecting one or more of the sets of optimization results for which the values of the energy control objective and the air quality control objective are not both improved by another of the sets of optimization results. 15 . A method for operating heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building, the method comprising: obtaining one or more predictive models configured to predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment; executing a multi-objective optimization process using the one or more predictive models to produce multiple sets of optimization results corresponding to different values of the control decision variables, the energy control objective, and the air quality control objective; selecting one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective; and operating the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results. 16 . The method of claim 15 , wherein the energy control objective comprises at least one of: an amount of energy consumption predicted to result from operating the HVAC equipment in accordance with the control decision variables; an amount of carbon emissions predicted to result from operating the HVAC equipment in accordance with the control decision variables; or a cost of energy consumed by the HVAC equipment predicted to result from operating the HVAC equipment in accordance with the control decision variables. 17 . The method of claim 15 , wherein the air quality control objective comprises at least one of: an infection risk predicted to result from operating the HVAC equipment in accordance with the control decision variables; an amount or concentration of particles in indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables; an indoor air quality score predicted to result from operating the HVAC equipment in accordance with the control decision variables; an amount or concentration of carbon dioxide in the indoor air in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables; or one or more comfort parameters affecting occupant comfort in the building predicted to result from operating the HVAC equipment in accordance with the control decision variables.

Assignees

Inventors

Classifications

  • G05B19/042Primary

    using digital processors (G05B19/05 takes precedence) · CPC title

  • F24F8/10Primary

    by separation, e.g. by filtering · CPC title

  • Responding to energy costs · CPC title

  • Indication arrangements, e.g. displays · CPC title

  • using pre-stored data · CPC title

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What does patent US2024176319A1 cover?
A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building is configured to obtain predictive models that predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment. The controller executes a multi-objective optimization process …
Who is the assignee on this patent?
Johnson Controls Tyco IP Holdings LLP
What technology area does this patent fall under?
Primary CPC classification G05B19/042. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu May 30 2024 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 7 related publications on this page (citations in our corpus or others sharing the same primary CPC).