Systems and methods for controlling a central plant for a building

• US 9,696,054 B2
• Filed: 03/23/2015
• Issued: 07/04/2017
• Est. Priority Date: 06/26/2012
• Status: Active Grant

• Current Assignee: Tyco Fire & Security GmbH (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Asmus, Matthew J.
• Primary Examiner(s): Patel, Ramesh
• Application Number:
  US14/666,119
• Publication Number:
  US 20150192317A1
• Time in Patent Office: 834 Days
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/47 Responding to energy costs
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/63 Electronic processing
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05D 23/1917 using digital means
• CPC Class Codes: G05F 1/66 Regulating electric power

Abstract

Systems and methods for controlling a central plant for a building are provided. The central plant has a plant load. An optimal combination of plant equipment for meeting the plant load is estimated. Estimating the optimal combination of plant equipment includes using binary optimization to determine at least two potential combinations of plant equipment. Estimating the optimal combination of plant equipment also includes using nonlinear optimization to determine a potential power consumption minimum for each of the at least two potential combinations. The central plant is controlled according to the estimated optimal combination of plant equipment.

Claims

1. A computerized method for controlling a central plant for a building, the central plant having a plant load, the method comprising:

estimating an optimal combination of plant equipment for meeting the plant load, wherein estimating the optimal combination of plant equipment comprises using binary optimization to determine at least two potential combinations of plant equipment and using nonlinear optimization to determine a potential power consumption minimum for each of the at least two potential combinations; and

controlling the central plant according to the estimated optimal combination of plant equipment.

2. The method of claim 1, wherein using binary optimization comprises:

identifying a first combination of devices to be turned; and

identifying at least a second combination of devices to be turned on,

wherein each combination minimizes a function of a power consumption of the central plant and provides energy to satisfy the plant load.

3. The method of claim 2, wherein a branch and bound method is used to identify the first combination of devices.

4. The method of claim 2, wherein identifying at least a second combination of devices comprises:

determining whether a first device of the first combination is on or off;

determining, if the first device is off, whether a second combination of a second device on and the first device off can provide the energy to satisfy the plant load;

identifying the second combination, if the first device is off and if the second combination can provide the energy to satisfy the plant load;

determining, if the first device is on, whether a third combination of the second device on and the first device on can provide the energy to satisfy the plant load;

determining, if the first device is on, whether a fourth combination of a third device on, the second device off, and the first device on can provide the energy to satisfy the plant load;

identifying the third combination, the fourth combination or both, if the first device is on and the third combination, the fourth combination, or both can provide the energy to satisfy the plant load.

5. The method of claim 4, wherein identifying at least a second combination of devices further comprises estimating the non-linear power consumption of at least one of the first combination, the second combination, the third combination, and the fourth combination using quadratic compensation.

6. The method of claim 1, wherein using nonlinear optimization comprises minimizing a function of a power consumption of the central plant using at least one of a Nelder-Mead method, a Generalized Reduced Gradient method, Sequential Quadratic Programming, a Steepest Descent method, and a Conjugate Gradient method.

7. A computerized method for controlling a central plant for a building, the method comprising:

identifying, at a processing circuit, a first combination of on/off statuses for a plurality of HVAC devices using non-exhaustive binary optimization;

identifying at least a second combination of on/off statuses for the plurality of HVAC devices;

identifying, for each of the first combination and at least a second combination, optimized operating setpoints for the plurality of HVAC devices using a non-linear optimization;

using the optimized operating setpoints identified with the non-linear optimization, estimating a likely energy consumption for the first combination of on/off statuses and at least a second combination of on/off statuses;

comparing the estimated likely energy consumption for the first combination of on/off statuses and at least a second combination of on/off statuses to determine which combination of HVAC devices to turn on; and

controlling the central plant according to the determined combination of HVAC devices to turn on.

8. The method of claim 7, wherein controlling the central plant according to the determined combination of HVAC devices comprises:

transmitting commands to the central plant using the on/off statuses of the determined combination of HVAC devices to turn on.

9. The method of claim 8, wherein controlling the central plant according to the determined combination of HVAC devices further comprises:

transmitting the identified optimized operating setpoints to the central plant for the determined combination of HVAC devices to turn on.

10. The method of claim 7, wherein the plurality of HVAC devices comprises at least one chiller, at least one evaporator pump, at least one condenser pump, and at least one cooling tower.

11. The method of claim 7, wherein the first combination and at least a second combination are estimated to provide energy required to satisfy a plant load.

12. The method of claim 7, wherein identifying at least a second combination of on/off statuses for the plurality of HVAC devices comprises:

determining whether a first device of the first combination is on or off;

determining, if the first device is off, a second combination of a second device on and the first device off;

determining, if the first device is on, a third combination of the second device on and the first device on;

determining, if the first device is on, a fourth combination of a third device on, the second device off, and the first device on;

identifying at least one of the second combination, the third combination, and the fourth combination when the second combination, the third combination, or the fourth combination is estimated to provide the energy required to satisfy the plant load.

13. The method of claim 12, wherein identifying at least a second combination of devices further comprises estimating the non-linear power consumption of at least one of the first combination, the second combination, the third combination, and the fourth combination using quadratic compensation.

14. The method of claim 12, wherein the first device consumes a least amount of energy and subsequent devices consume progressively greater amounts of energy.

15. The method of claim 7, wherein the operating setpoints comprise at least one of a supply water temperature setpoint, a condenser water temperature setpoint, and a return water temperature setpoint.

16. The method of claim 7, wherein binary optimization comprises a branch and bound method.

17. The method of claim 7, wherein non-linear optimization comprises at least one of a Nelder-Mead method, a Generalized Reduced Gradient method, Sequential Quadratic Programming, a Steepest Descent method, and a Conjugate Gradient method.

18. The method of claim 7, wherein the optimum operating setpoints minimize energy consumption of the central plant.

19. The method of claim 7, wherein the first combination and at least a second combination satisfy constraints on the central plant.

20. The method of claim 19, wherein the constraints comprise at least one of:

operating the central plant with an energy consumption below a maximum energy consumption; and

operating any one device with an energy consumption above a minimum energy consumption.

21. The method of claim 7, further comprising outputting an indication of the on/off statuses and optimum operating setpoints to at least one of a memory device, a user device, or another device on a building management system.

22. A controller for controlling a central plant for a building, the central plant having a plant load, the controller comprising:

a processing circuit configured to estimate an optimal combination of plant equipment for meeting the plant load, wherein estimating the optimal combination of plant equipment comprises using binary optimization to determine at least two potential combinations of plant equipment and using nonlinear optimization to determine a potential power consumption minimum for each of the at least two potential combinations; and

wherein the processing circuit is further configured to control the central plant according to the estimated optimal combination of plant equipment.

23. The controller of claim 22, wherein using binary optimization comprises:

identifying a first combination of equipment to be turned; and

identifying at least a second combination of equipment to be turned on,

wherein each combination minimizes a function of a power consumption of the central plant and provides energy to satisfy the plant load.

24. The controller of claim 23, wherein a branch and bound method is used to identify the first combination of equipment.

25. The controller of claim 23, wherein identifying at least a second combination of equipment comprises:

determining whether a first device of the first combination is on or off;

determining, if the first device is off, whether a second combination of a second device on and the first device off can provide the energy to satisfy the plant load;

identifying the second combination, if the first device is off and if the second combination can provide the energy to satisfy the plant load;

determining, if the first device is on, whether a third combination of the second device on and the first device on can provide the energy to satisfy the plant load;

determining, if the first device is on, whether a fourth combination of a third device on, the second device off, and the first device on can provide the energy to satisfy the plant load;

identifying the third combination, the fourth combination or both, if the first device is on and the third combination, the fourth combination, or both can provide the energy to satisfy the plant load.

26. The controller of claim 25, wherein identifying at least a second combination of devices further comprises estimating the non-linear power consumption of at least one of the first combination, the second combination, the third combination, and the fourth combination using quadratic compensation.

27. The controller of claim 22, wherein using nonlinear optimization comprises minimizing a function of a power consumption of the central plant using at least one of a Nelder-Mead method, a Generalized Reduced Gradient method, Sequential Quadratic Programming, a Steepest Descent method, and a Conjugate Gradient method.