Systems and methods for cascaded model predictive control

• US 9,852,481 B1
• Filed: 03/13/2013
• Issued: 12/26/2017
• Est. Priority Date: 03/13/2013
• Status: Active Grant

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Turney, Robert D., Wenzel, Michael J.
• Primary Examiner(s): Flynn, Kevin
• Assistant Examiner(s): Zeroual, Omar
• Application Number:
  US13/802,154
• Time in Patent Office: 1,749 Days
• Field of Search: 705112
• CPC Class Codes: G06Q 20/085 involving remote charge determination or related payment systems
• CPC Class Codes: G06Q 20/145 Payments according to the detected use or quantity
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

Methods and systems to minimize energy cost in response to time-varying energy prices are presented for a variety of different pricing scenarios. A cascaded model predictive control system is disclosed comprising an inner controller and an outer controller. The inner controller controls power use using a derivative of a temperature setpoint and the outer controller controls temperature via a power setpoint or power deferral. An optimization procedure is used to minimize a cost function within a time horizon subject to temperature constraints, equality constraints, and demand charge constraints. Equality constraints are formulated using system model information and system state information whereas demand charge constraints are formulated using system state information and pricing information. A masking procedure is used to invalidate demand charge constraints for inactive pricing periods including peak, partial-peak, off-peak, critical-peak, and real-time.

Claims

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

a building system comprising one or more measurement devices configured to measure at least one of a temperature of the building and a power usage of the building, wherein the building system is configured to generate a feedback signal comprising at least one of the measured temperature of the building and the measured power usage of the building;

a load predictor configured to predict a future power usage of the building based on historical weather and power usage data;

an outer model predictive controller configured to receive the feedback signal from the building system, receive time-varying pricing information for a plurality of pricing scenarios, perform an optimization process to determine an optimal amount of power to defer from the predicted power usage based on the feedback signal and the pricing information, and output a power control signal indicating the optimal amount of power to defer, wherein the optimal amount of power to defer optimizes a total cost of the power usage of the building;

an inner model predictive controller configured to receive the feedback signal from the building system, receive a power setpoint representing a difference between the predicted power usage and the optimal amount of power to defer, determine a temperature setpoint for the building system predicted to achieve the power setpoint, and output a temperature control signal indicating the temperature setpoint; and

HVAC equipment comprising one or more physical devices configured to supply heat to the building or remove heat from the building, wherein the building system is configured to operate the HVAC equipment to achieve the temperature setpoint;

wherein at least one of the outer model predictive controller and the inner model predictive controller is an electronic device comprising a communications interface and a processing circuit.

2. The HVAC system of claim 1, wherein the feedback signal includes both information representative of the measured temperature and information representative of the measured power usage of the building.

3. The HVAC system of claim 2, wherein the outer model predictive controller is configured to:

Receive a dynamic model describing heat transfer characteristics of the building and temperature constraints defining an acceptable range for the measured temperature;

Use the dynamic model and the feedback signal to estimate a temperature state for the building as a function of power usage; and

Use an optimization procedure to determine a power usage for the building which minimizes the total cost of the power usage while maintaining the estimated temperature state within the acceptable range.

4. The HVAC system of claim 1, wherein the outer model predictive controller and the inner controller have different sampling and control intervals, wherein the sampling and control interval of the outer model predictive controller is longer than the sampling and control interval of the inner model predictive controller.

5. The HVAC system of claim 1, wherein the outer model predictive controller and the inner model predictive controller are physically decoupled in location.

6. The HVAC system of claim 1, wherein the time-varying pricing information includes demand charge information defining a cost per unit of power corresponding to a maximum power usage within a pricing period.

7. The HVAC system of claim 6, wherein the time varying pricing information includes demand charge information for two or more of thea plurality of pricing periods.

8. The HVAC system of claim 1, wherein the temperature control signal includes at least one of:

the temperature setpoint, and

a derivative of the temperature setpoint.

9. The HVAC system of claim 1, wherein the power control signal includes at least one of:

the power setpoint received by the inner model predictive controller, and

the amount of power to defer from a predicted power usage, wherein the amount of power to defer is subtracted from the predicted power usage to calculate the power setpoint received by the inner model predictive controller.

10. The HVAC system of claim 9, wherein the load predictor configured to:

receive the temperature setpoint and at least one of;

current weather information, past weather information, and past building power usage, and

output the predicted power usage, wherein the power control signal is an amount of power to defer from the predicted power usage.