SMART THERMOSTAT WITH MODEL PREDICTIVE CONTROL

• US 20190078801A1
• Filed: 11/09/2018
• Published: 03/14/2019
• Est. Priority Date: 04/28/2017
• Status: Active Grant

• Current Assignee: Tyco Fire & Security GmbH (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Turney, Robert D., Ellis, Matthew J., Wenzel, Michael J., ElBsat, Mohammad N., Bernal, Juan Esteban Tapiero, Fentzlaff, Brennan H.
• Granted Patent: US 10,495,337 B2
• Time in Patent Office: Days
• CPC Class Codes: F24F 11/00 Control or safety arrangements
• 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 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 11/47 Responding to energy costs
• CPC Class Codes: F24F 11/52 Indication arrangements, e.g. displays
• CPC Class Codes: F24F 11/58 using Internet communication
• 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 11/64 using pre-stored data
• CPC Class Codes: F24F 11/65 for selecting an operating mode
• CPC Class Codes: F24F 11/89 Arrangement or mounting of control or safety devices
• CPC Class Codes: F24F 2110/10 Temperature
• CPC Class Codes: F24F 2110/12 of the outside air
• CPC Class Codes: F24F 2130/10 Weather information or forecasts
• CPC Class Codes: F24F 2140/50 Load
• CPC Class Codes: F24F 2140/60 Energy consumption
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05D 23/1904 variable in time
• CPC Class Codes: G05D 23/1917 using digital means
• CPC Class Codes: G05D 23/1923 : using thermal energy, the cost of which varies in function of time

Abstract

A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

Claims

1. A system for monitoring and controlling temperature of a building zone, the system comprising:

a model predictive controller configured to;

obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps in a period to provide heating or cooling to the building zone;

use a predictive model to predict the temperature of the building zone during each of the plurality of time steps as a function of temperature setpoints for a thermostat for the building zone; and

generate the temperature setpoints for the thermostat for the building zone for each of the plurality of time steps by performing an operation of the cost function subject to a constraint on the temperature of the building zone predicted by the predictive model;

an equipment controller configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

2. The system of claim 1, wherein the operation is an optimization and the model predictive controller is configured to determine the cost of operating the HVAC equipment during each of the plurality of time steps using a set of time-varying utility rates comprising a utility rate value for each time step;

wherein the time-varying utility rates are received from a utility provider or predicted by the model predictive controller.

3. The system of claim 1, wherein the model predictive controller is separate from the thermostat and configured to provide the temperature setpoints to the thermostat via a communications network.

4. The system of claim 1, wherein the equipment controller is configured to:

receive user-provided temperature setpoints via a local user interface of the thermostat or a mobile device in communication with the thermostat; and

in response to receiving the user-provided temperature setpoints, override the temperature setpoints generated by the model predictive controller with the user-provided temperature setpoints and use the user-provided temperature setpoints to operate the HVAC equipment.

5. The system of claim 1, wherein the model predictive controller is configured to generate the predictive model by performing a system identification process comprising:

modulating the temperature setpoints within a constrained temperature setpoint range;

collecting a set of input-output data comprising values of the temperature setpoints and values of the temperature of the building zone that result from modulating the temperature setpoints during each of a plurality of time steps of a learning period; and

fitting parameters of the predictive model to the set of input-output data.

6. The system of claim 1, wherein the predictive model comprises a thermal mass storage model that defines the temperature of the building zone as a function of at least one of:

heat transfer between air within the building zone and solid mass within the building zone;

heat transfer between the building zone and the HVAC equipment; and

an unmeasured heat load disturbance.

7. The system of claim 6, wherein the model predictive controller is configured to predict a value of the unmeasured heat load disturbance experienced by the building zone at each of the plurality of time steps in the period.

8. The system of claim 1, wherein the predictive model comprises an HVAC load model that defines the heating or cooling provided by the HVAC equipment as a function of the temperature of the building zone and at least one of the temperature setpoints.

9. The system of claim 1, wherein the model predictive controller is configured to predict the cost of operating the HVAC equipment as a function of an amount of the heating or cooling provided by the HVAC equipment at each time step of the period.

10. The system of claim 1, wherein the constraint on the temperature of the building zone predicted by the predictive model requires the model predictive controller to maintain the temperature of the building zone predicted by the predictive model within:

a first zone temperature range during a first time step of the period; and

a second zone temperature range, different from the first zone temperature range, during another time step of the period subsequent to the first time step.

11. A method performed at least partially by a thermostat for a building zone for monitoring and controlling temperature of the building zone, the method comprising:

obtaining a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps in a period to provide heating or cooling to the building zone;

using a predictive model to predict the temperature of the building zone during each of the plurality of time steps as a function of temperature setpoints for a thermostat for the building zone;

generating the temperature setpoints for the thermostat for the building zone for each of the plurality of time steps by performing an operation of the cost function subject to a constraint on the temperature of the building zone predicted by the predictive model;

operating the HVAC equipment to provide heating or cooling to the building zone during each of the plurality of time steps to drive the temperature of the building zone toward the temperature setpoints.

12. The method of claim 11, wherein the operation is an optimization, the method further comprising:

receiving a set of time-varying utility rates from a utility provider or predicting the time-varying utility rates, the set of time-varying utility rates comprising a utility rate value for each time step; and

determining the cost of operating the HVAC equipment during each of the plurality of time steps using the set of time-varying utility rates.

13. The method of claim 11, wherein the temperature setpoints are generated by a model predictive controller separate from the thermostat and provided to the thermostat via a communications network.

14. The method of claim 11, further comprising:

receiving user-provided temperature setpoints via a local user interface of the thermostat or a mobile device in communication with the thermostat; and

in response to receiving the user-provided temperature setpoints, overriding the temperature setpoints generated by the model predictive controller with the user-provided temperature setpoints and using the user-provided temperature setpoints to operate the HVAC equipment.

15. The method of claim 11, further comprising generating the predictive model by performing a system identification process comprising:

modulating the temperature setpoints within a constrained temperature setpoint range;

collecting a set of input-output data comprising values of the temperature setpoints and values of the temperature of the building zone that result from modulating the temperature setpoints during each of a plurality of time steps of a learning period; and

fitting parameters of the predictive model to the set of input-output data.

16. The method of claim 11, wherein the predictive model comprises a thermal mass storage model that defines the temperature of the building zone as a function of at least one of:

heat transfer between air within the building zone and solid mass within the building zone;

heat transfer between the building zone and the HVAC equipment; and

an unmeasured heat load disturbance.

17. The method of claim 16, further comprising predicting a value of the unmeasured heat load disturbance experienced by the building zone at each of the plurality of time steps in the period.

18. The method of claim 11, wherein the predictive model comprises an HVAC load model that defines the heating or cooling provided by the HVAC equipment as a function of the temperature of the building zone and at least one of the temperature setpoints.

19. The method of claim 11, further comprising predicting the cost of operating the HVAC equipment as a function of an amount of the heating or cooling provided by the HVAC equipment at each time step of the period.

20. A system for monitoring and controlling temperature of a building zone, the system comprising:

a model predictive controller configured to;

obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps in an optimization period to provide heating or cooling to the building zone; and

generate temperature setpoints for the building zone for each of the plurality of time steps by performing an optimization of the cost function subject to a constraint on a predicted temperature of the building zone, wherein the predicted temperature is defined by a predictive model as a function of the temperature setpoints;

a thermostat for the building zone, the thermostat configured to;

receive the temperature setpoints generated by the model predictive controller via a communications network; and

drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.