Systems and methods for optimal energy use and carbon emissions using hierarchical model predictive control (mpc)

Patent metadata

Field	Value
Publication number	US-2024255907-A1
Application number	US-202318160433-A
Country	US
Kind code	A1
Filing date	Jan 27, 2023
Priority date	Jan 27, 2023
Publication date	Aug 1, 2024
Grant date	—

Abstract

A method for optimizing carbon emissions and/or energy usage of a site is disclosed comprising: obtaining a planning model for optimizing carbon emissions and/or energy usage of the site at a site-wide model predictive control (MPC) controller; sending at least one optimization request from the site-wide MPC controller to one or more unit MPC controllers; receiving at least one proxy limit value from the one or more unit MPC controllers at the site-wide MPC controller in response to the at least one optimization request, wherein the at least one proxy limit value identifies an extent to which one or more controlled variables controlled by the one or more unit MPC controllers are adjustable without violating one or more controlled variable constraints;and performing site-wide optimization at the site-wide MPC controller using the planning model and the at least one proxy limit value.

First claim

What is claimed is:

1 . A computer-implemented method for optimizing carbon emissions and/or energy usage of a site comprising:
obtaining a planning model for optimizing carbon emissions and/or energy usage of the site at a site-wide model predictive control (MPC) controller; sending at least one optimization request from the site-wide MPC controller to one or more unit MPC controllers; receiving at least one proxy limit value from the one or more unit MPC controllers at the site-wide MPC controller in response to the at least one optimization request, wherein the at least one proxy limit value identifies an extent to which one or more controlled variables controlled by the one or more unit MPC controllers are adjustable without violating one or more controlled variable constraints; and performing site-wide optimization at the site-wide MPC controller using the planning model and the at least one proxy limit value, wherein the one or more controlled variables includes at least one of temperature, humidity, and ventilation flow rate.

2 . The method of claim 1 , wherein receiving the at least one proxy limit value comprises receiving at least one proxy limit value that is based on one or more MPC models used by the one or more unit MPC controllers.

3 . The method of claim 2 , wherein the unit MPC controllers control one or more actuators used to control one or more manipulated variables, wherein changes to the one or manipulated variables result in changes to the one or more controlled variables.

4 . The method of claim 3 , wherein the one or more actuators includes an actuator for adjusting the damper position of an HVAC system.

5 . The method of claim 1 , wherein each proxy limit value identifies a maximum or minimum value obtainable for one of the one or more controlled variable without violating any controlled variable constraints.

6 . The method of claim 1 , wherein the site-wide MPC controller during the site-wide optimization generates a real-time planning solution within a closed-loop control system.

7 . The method of claim 1 , wherein the site includes at least one of a building, a warehouse, and a campus.

8 . A system for optimizing carbon emissions and/or energy usage of a site comprising:
a site-wide model predictive control (MPC) controller comprising:
at least one memory configured to store a planning model for an industrial facility;
at least one network interface configured to communicate with one or more unit MPC controllers; and
at least one processing device configured to:
obtain a planning model for optimizing carbon emissions and/or energy usage of the site;
send at least one optimization request to one or more unit MPC controllers;
receive at least one proxy limit value from the one or more unit MPC controllers in response to the at least one optimization request, wherein the at least one proxy limit value identifies an extent to which one or more controlled variables controlled by the one or more unit MPC controllers are adjustable without violating one or more controlled variable constraints; and
perform site-wide optimization using the planning model and the at least one proxy limit value, wherein the one or more controlled variables includes at least one of temperature, humidity, and ventilation flow rate.

9 . The system of claim 8 , wherein receiving the at least one proxy limit value comprises receiving at least one proxy limit value that is based on one or more MPC models used by the one or more unit MPC controllers.

10 . The system of claim 9 , wherein the unit MPC controllers control one or more actuators used to control one or more manipulated variables, wherein changes to the one or manipulated variables result in changes to the one or more controlled variables.

11 . The system of claim 10 , wherein the one or more actuators includes an actuator for adjusting the damper position of an HVAC system.

12 . The method of claim 8 , wherein each proxy limit value identifies a maximum or minimum value obtainable for one controlled variable without violating any controlled variable constraints.

13 . The method of claim 8 , wherein the site-wide MPC controller during the site-wide optimization generates a real-time planning solution within a closed-loop control system.

14 . The method of claim 8 , wherein the site includes at least one of a building, a warehouse, and a campus.

15 . A non-transitory computer-readable medium containing instructions for optimizing carbon emissions and/or energy usage of a site, the non-transitory computer-readable medium storing instructions that, when executed by at least one processor, configure the at least one processor for:
obtaining a planning model for optimizing carbon emissions and/or energy usage of the site at a site-wide model predictive control (MPC) controller; sending at least one optimization request from the site-wide MPC controller to one or more unit MPC controllers; receiving at least one proxy limit value from the one or more unit MPC controllers at the site-wide MPC controller in response to the at least one optimization request, wherein the at least one proxy limit value identifies an extent to which one or more controlled variables controlled by the one or more unit MPC controllers are adjustable without violating one or more controlled variable constraints; and performing site-wide optimization at the site-wide MPC controller using the planning model and the at least one proxy limit value, wherein the one or more controlled variables includes at least one of temperature, humidity, and ventilation flow rate.

16 . The non-transitory computer-readable medium of claim 15 , wherein receiving the at least one proxy limit value comprises receiving at least one proxy limit value that is based on one or more MPC models used by the one or more unit MPC controllers.

17 . The non-transitory computer-readable medium of claim 16 , wherein the unit MPC controllers control one or more actuators used to control one or more manipulated variables, wherein changes to the one or manipulated variables result in changes to the one or more controlled variables.

18 . The non-transitory computer-readable medium of claim 17 , wherein the one or more actuators includes an actuator for adjusting the damper position of an HVAC system.

19 . The non-transitory computer-readable medium of claim 15 , wherein each proxy limit value identifies a maximum or minimum value obtainable for one controlled variable without violating any controlled variable constraints.

20 . The non-transitory computer-readable medium of claim 15 , wherein the site-wide MPC controller during the site-wide optimization generates a real-time planning solution within a closed-loop control system.

Assignees

• Honeywell Int Inc

Inventors

• Majewski Joseph
• Pai Ramdas
• Lu Joseph

Classifications

• G05B2219/2614

  HVAC, heating, ventillation, climate control · CPC title

• G05B19/042 Primary

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

• G06N5/022 Primary

  Knowledge engineering; Knowledge acquisition · CPC title

• G05B2219/2639

  Energy management, use maximum of cheap power, keep peak load low · CPC title