IP Library Granted Patent US 12,007,732
Granted Patent B2
US 12,007,732 · App. 17/403,669 · Granted Jun 11, 2024

HVAC system with building infection control

Inventors: Michael J. Risbeck (Madison, WI); Kirk H. Drees (Cedarburg, WI); Jonathan D. Douglas (Mequon, WI)
Assignee: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
G05B19/042F24F8/10F24F11/47F24F11/52F24F11/64F24F11/70F24F8/22F24F2110/10F24F2110/20F24F2120/20F24F2140/60G05B15/02G05B19/04G05B2219/2614G06F30/20
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Quick Facts
Patent No.
US 12,007,732
App. No.
17/403,669
Granted
Jun 11, 2024
Kind
B2
Abstract

A heating, ventilation, or air conditioning (HVAC) system for one or more building zones includes airside HVAC equipment that provide air to the one or more building zones and a controller. The controller obtains predictive models to predict values of a first control objective and a second control objective for the one or more building zones as a function of control decision variables for the airside HVAC equipment. The controller performs a Pareto optimization for a time period using the one or more predictive models to determine multiple sets of Pareto optimal values of the control decision variables and corresponding sets of Pareto optimal values of the first control objective and the second control objective for the time period. The controller operates the airside HVAC equipment to provide the air to the one or more building zones in accordance with a selected set of the Pareto optimal values.

Claims (67)

1. A heating, ventilation, or air conditioning (HVAC) system for one or more building zones, the HVAC system comprising:

airside HVAC equipment operable to provide air to the one or more building zones, the airside HVAC equipment comprising one or more air handling units, rooftop units, or variable air volume units; and

a controller configured to:

obtain one or more predictive models configured to predict values of a first control objective and a second control objective for the one or more building zones as a function of control decision variables for the airside HVAC equipment, the first control objective comprising an indication of infection risk that results from a predicted concentration of airborne infectious quanta, the indication of infection risk predicted by an infectious quanta model as a function of the control decision variables, the control decision variables for the airside HVAC equipment comprising at least one of a supply air temperature setpoint, a minimum ventilation setpoint for the one or more building zones, whether to operate ultraviolet (UV) disinfection devices or standalone in-zone filtration units, or a type of filter to be used in the airside HVAC equipment;

perform a Pareto optimization for a time period using the one or more predictive models to determine a plurality of sets of Pareto optimal values of the control decision variables and corresponding sets of Pareto optimal values of the first control objective and the second control objective for the time period;

provide a user interface comprising multiple selectable control plan options, the user interface comprising for each of the multiple selectable control plan options (i) a set of the Pareto optimal values of the control decision variables and (ii) a corresponding set of the Pareto optimal values of the first control objective and the second control objective predicted to result from the set of the Pareto optimal values of the control decision variables; and

operate the airside HVAC equipment to provide the air to the one or more building zones in accordance with a set of the Pareto optimal values of the control decision variables over the time period corresponding to a control plan option of the multiple selectable control plan options selected via the user interface;

wherein the infectious quanta model is a dynamic infectious quanta model and the second control objective comprises an energy metric predicted by an energy model as a second function of the control decision variables for the airside HVAC equipment.

2. The HVAC system of claim 1 , wherein performing the Pareto optimization comprises:

obtaining multiple sets of values of the control decision variables for the time period;

using the one or more predictive models to predict, for each of the multiple sets of values of the control decision variables, corresponding values of the first control objective and the second control objective; and

selecting a subset of the multiple sets of values of the control decision variables as the Pareto optimal values of the control decision variables based on the corresponding values of the first control objective and the second control objective.

3. The HVAC system of claim 1 , wherein the controller is configured to select from the plurality of sets of Pareto optimal values of the control decision variables based on the corresponding sets of Pareto optimal values of the first control objective and the second control objective at least:

a first set of Pareto optimal values of the control decision variables that prioritizes the first control objective over the second control objective provided as a first of the multiple selectable control plan options;

a second set of Pareto optimal values of the control decision variables that prioritizes the second control objective over the first control objective provided as a second of the multiple selectable control plan options; and

a third set of Pareto optimal values of the control decision variables that balances the first control objective and the second control objective provided as a third of the multiple selectable control plan options.

4. The HVAC system of claim 3 , wherein the controller is configured to:

present the at least first set, second set, and third set of Pareto optimal values of the control decision variables, corresponding values of the first control objective and the second control objective, and corresponding values of the control decision variables as the multiple selectable control plan options via the user interface; and

receive the selected set of the Pareto optimal values of the control decision variables as an input responsive to a user selecting one of the multiple selectable control plan options via the user interface.

5. The HVAC system of claim 1 , wherein the controller is configured to perform an analysis of a previous time period using the one or more predictive models to determine an analysis set of values of the first control objective and the second control objective as a function of values of the control decision variables over the previous time period.

6. The HVAC system of claim 5 , wherein the controller is configured to operate a display to provide the analysis set of values of the first control objective and the second control objective for the previous time period concurrently with the Pareto optimal values of the first control objective and the second control objective for the time period.

7. A controller for a heating, ventilation, or air conditioning (HVAC) system 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 a first control objective and a second control objective for one or more building zones of the building as a function of control decision variables for the HVAC system, the first control objective comprising an indication of infection risk that results from a predicted concentration of airborne infectious quanta, the indication of infection risk predicted by an infectious quanta model as a function of the control decision variables, wherein the HVAC system comprises one or more air handling units, rooftop units, or variable air volume units and wherein the control decision variables comprise at least one of a supply air temperature setpoint or a minimum ventilation setpoint for the one or more building zones, whether to operate ultraviolet (UV) disinfection devices or standalone in-zone filtration units, or a type of filter to be used in the HVAC system;

performing an analysis of a previous time period using the one or more predictive models to determine an analysis set of values of the first control objective and the second control objective as a function of values of the control decision variables over the previous time period;

performing a Pareto optimization for a future time period using the one or more predictive models to determine a plurality of sets of Pareto optimal values of the control decision variables and corresponding sets of Pareto optimal values of the first control objective and the second control objective for the future time period; and

providing a user interface comprising multiple selectable control plan options, the user interface comprising for each of the multiple selectable control plan options (i) a set of the Pareto optimal values of the control decision variables and (ii) a corresponding set of the Pareto optimal values of the first control objective and the second control objective predicted to result from the set of the Pareto optimal values of the control decision variables;

wherein the infectious quanta model is a dynamic infectious quanta model and the second control objective comprises an energy metric predicted by an energy model as a second function of the control decision variables for the HVAC system.

8. The controller of claim 7 , wherein performing the Pareto optimization comprises:

obtaining multiple sets of values of the control decision variables for the future time period;

using the one or more predictive models to predict, for each of the multiple sets of values of the control decision variables, corresponding values of the first control objective and the second control objective; and

selecting a subset of the multiple sets of values of the control decision variables as the Pareto optimal values of the control decision variables based on the corresponding values of the first control objective and the second control objective.

9. The controller of claim 7 , wherein the controller is configured to select from the plurality of sets of Pareto optimal values of the control decision variables based on the corresponding sets of Pareto optimal values of the first control objective and the second control objective at least:

a first set of Pareto optimal values of the control decision variables that prioritizes the first control objective over the second control objective provided as a first of the multiple selectable control plan options;

a second set of Pareto optimal values of the control decision variables that prioritizes the second control objective over the first control objective provided as a second of the multiple selectable control plan options; and

a third set of Pareto optimal values of the control decision variables that balances the first control objective and the second control objective provided as a third of the multiple selectable control plan options.

10. The controller of claim 9 , wherein the controller is configured to:

receive a selection of the multiple selectable control plan options via the user interface; and

operate the HVAC system in accordance with a set of Pareto optimal values of the control decision variables corresponding to the selection of the multiple selectable control plan options.

11. A method for operating a heating, ventilation, or air conditioning (HVAC) system for one or more building zones, method comprising:

obtaining one or more predictive models configured to predict values of a first control objective and a second control objective for the one or more building zones as a function of control decision variables for airside HVAC equipment, the first control objective comprising an indication of infection risk that results from a predicted concentration of airborne infectious quanta, the indication of infection risk predicted by an infectious quanta model as a function of the control decision variables, the airside HVAC equipment comprising one or more air handling units, rooftop units, or variable air volume units, the control decision variables for the airside HVAC equipment comprising at least one of a supply air temperature setpoint, a minimum ventilation setpoint for the one or more building zones, whether to operate ultraviolet (UV) disinfection devices or standalone in-zone filtration units, or a type of filter to be used in the airside HVAC equipment;

performing a Pareto optimization for a time period using the one or more predictive models to determine a plurality of sets of Pareto optimal values of the control decision variables and corresponding sets of Pareto optimal values of the first control objective and the second control objective for the time period;

providing a user interface comprising multiple selectable control plan options, the user interface comprising for each of the multiple selectable control plan options (i) a set of the Pareto optimal values of the control decision variables and (ii) a corresponding set of the Pareto optimal values of the first control objective and the second control objective predicted to result from the set of the Pareto optimal values of the control decision variables; and

operating the airside HVAC equipment to provide the air to the one or more building zones in accordance with a set of the Pareto optimal values of the control decision variables over the time period corresponding to a control plan option of the multiple selectable control plan options selected via the user interface;

wherein the infectious quanta model is a dynamic infectious quanta model and the second control objective comprises an energy metric predicted by an energy model as a second function of the control decision variables for the airside HVAC equipment.

12. The method of claim 11 , wherein performing the Pareto optimization comprises:

obtaining multiple sets of values of the control decision variables for the time period;

using the one or more predictive models to predict, for each of the multiple sets of values of the control decision variables, corresponding values of the first control objective and the second control objective; and

selecting a subset of the multiple sets of values of the control decision variables as the Pareto optimal values of the control decision variables based on the corresponding values of the first control objective and the second control objective.

13. The method of claim 11 , further comprising selecting from the plurality of sets of Pareto optimal values of the control decision variables based on the corresponding sets of Pareto optimal values of the first control objective and the second control objective:

a first set of Pareto optimal values of the control decision variables that prioritizes the first control objective over the second control objective provided as a first of the multiple selectable control plan options;

a second set of Pareto optimal values of the control decision variables that prioritizes the second control objective over the first control objective provided as a second of the multiple selectable control plan options; and

a third set of Pareto optimal values of the control decision variables that balances the first control objective and the second control objective provided as a third of the multiple selectable control plan options.

14. The method of claim 13 , further comprising:

presenting the first set, second set, and third set of Pareto optimal values of the control decision variables corresponding values of the first control objective and the second control objective, and corresponding values of the control decision variables as the multiple selectable control plan options via the user interface; and

receiving the selected set of the Pareto optimal values of the control decision variables as an input responsive to a user selecting one of the multiple selectable control plan options via the user interface.

15. A controller for a heating, ventilation, or air conditioning (HVAC) system 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 a first control objective and a second control objective for one or more building zones of the building as a function of control decision variables for the HVAC system, the first control objective comprising an indication of infection risk that results from a predicted concentration of airborne infectious quanta, the indication of infection risk predicted by an infectious quanta model as a function of the control decision variables, the HVAC system including one or more air handling units, rooftop units, or variable air volume units, wherein the control decision variables for the HVAC system comprise at least one of a supply air temperature setpoint, a minimum ventilation setpoint for the one or more building zones, whether to operate ultraviolet (UV) disinfection devices or standalone in-zone filtration units, or a type of filter to be used in the HVAC system;

performing an analysis of a previous time period using the one or more predictive models to determine an analysis set of values of the first control objective and the second control objective as a function of values of the control decision variables over the previous time period;

performing a Pareto optimization for a future time period using the one or more predictive models to determine a plurality of sets of Pareto optimal values of the control decision variables and corresponding sets of Pareto optimal values of the first control objective and the second control objective for the future time period;

selecting two or more of the sets of the Pareto optimal values of the control decision variables and corresponding Pareto optimal values of the first control objective and the second control objective based on the Pareto optimal values of the first control objective and the second control objective; and

providing a user interface comprising two or more selectable control plan options corresponding to the selected two or more sets of the Pareto optimal values of the control decision variables and corresponding Pareto optimal values of the first control objective and the second control objective, the two or more selectable control plan options also comprising a predicted energy cost for each of the two or more selectable control plan options; and

operating the HVAC system to affect an environmental condition of the building in accordance with the values of the control decision variables corresponding to a set of the Pareto optimal values of the control decision variables and corresponding Pareto optimal values of the first control objective and the second control objective corresponding to a control plan selected via the user interface;

wherein the infectious quanta model is a dynamic infectious quanta model and the second control objective comprises an energy metric predicted by an energy model as a second function of the control decision variables for the HVAC system.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 18, 2024
From: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
To: TYCO FIRE & SECURITY GMBH
Reel/Frame 066957/0796 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 16, 2021
From: RISBECK, MICHAEL J.; DREES, KIRK H.; DOUGLAS, JONATHAN D.
To: JOHNSON CONTROLS TYCO IP HOLDINGS LLP
Reel/Frame 057194/0923 →