Granted Patent B2

US 11,036,249 · App. 16/383,228 · Granted Jun 15, 2021

Inventor: Mohammad N. ElBsat (Milwaukee, WI)

Assignee: Johnson Controls Technology Company

G05F1/66G05B13/026G05B15/02G06Q10/04G06Q50/06H02J3/32H02J7/0068H02J13/0006G05B2219/2614G05B2219/2642H02J3/003

Abstract

Claims (54)

1. A central plant comprising:

one or more storage devices configured to store one or more resources purchased from a utility or generated by the central plant and to discharge the one or more resources for use in satisfying a building load; and

a controller configured to:

obtain a cost function comprising a peak load contribution (PLC) term, wherein the PLC term represents a cost based on an amount of the one or more resources purchased from the utility during coincidental peak (CP) hours of an optimization period comprising a plurality of time steps, the CP hours comprising a subset of the plurality of time steps, wherein the cost is a function of one or more decision variables representing an amount of the one or more resources to store in the one more storage devices or discharge from the one or more storage devices during each of the plurality of time steps;

modify the cost function by applying a peak hours mask to the PLC term, wherein the peak hours mask identifies one or more hours in the optimization period as projected peak hours and causes the controller to assign substantially zero cost, in the PLC term, to the one or more resources purchased from the utility during any hours not identified as projected peak hours; and

allocate, to each of the time steps within the optimization period, an amount of the one or more resources to store in the one or more storage devices or discharge from the one or more storage devices during the time step by performing an optimization of the modified cost function to determine values of the decision variables.

2. The central plant of claim 1 , wherein the CP hours comprise one or more hours of the optimization period during which regional demand peaks occur for a geographic region in which the building is located.

3. The central plant of claim 1 , wherein:

the CP hours are unknown prior to the optimization period; and

the projected peak hours comprise an estimate of the CP hours and are identified prior to the optimization period.

4. The central plant of claim 1 , wherein the peak hours mask comprises a vector of binary values, each of the binary values corresponding to an hour of the optimization period and indicating whether the corresponding hour is a projected peak hour.

5. The central plant of claim 1 , wherein the controller is configured to create the peak hours mask based on user input defining the projected peak hours.

6. The central plant of claim 1 , wherein the controller is configured to:

predict regional demand peaks for a geographic region in which the building is located;

define the projected peak hours based on the predicted regional demand peaks; and

create the peak hours mask using the projected peak hours.

7. The central plant of claim 6 , wherein the controller is configured to predict the regional demand peaks based on at least one of load history data and weather data for the geographic region in which the building is located.

8. The central plant of claim 1 , wherein:

the PLC term comprises a rate factor defining a cost per unit of the one or more resources purchased from the utility during the CP hours; and

the controller is configured to:

identify a geographic region in which the building is located; and

calculate the rate factor based on one or more parameters that depend on the identified geographic region.

9. The central plant of claim 1 , wherein the one or more one or more storage devices comprise one or more of a hot water storage tank or a cold thermal energy storage tank.

10. The central plant of claim 1 , wherein the one or more resources comprise one or more of hot water, cold water, or steam.

11. A method for allocating one or more resources in a central plant, the method comprising:

obtaining a cost function comprising a peak load contribution (PLC) term, wherein the PLC term represents a cost based on an amount of the one or more resources purchased from the utility during coincidental peak (CP) hours of an optimization period comprising a plurality of time steps, the CP hours comprising a subset of the plurality of time steps, wherein the cost is a function of one or more decision variables representing an amount of the one or more resources to store in one or more storage devices or to discharge from the one or more storage devices during each of the plurality of time steps;

modifying the cost function by applying a peak hours mask to the PLC term, wherein the peak hours mask identifies one or more hours in the optimization period as projected peak hours and causes the one or more resources purchased from the utility during any hours not identified as projected peak hours to be assigned substantially zero cost in the PLC term;

allocating, to each of the time steps within the optimization period, an amount of the one or more resources to store in the one or more storage devices or discharge from the one or more storage devices during the time step by performing an optimization of the modified cost function to determine values of the decision variables.

12. The method of claim 11 , wherein the CP hours comprise one or more hours of the optimization period during which regional demand peaks occur for a geographic region in which the building is located.

13. The method of claim 11 , wherein:

the CP hours are unknown prior to the optimization period; and

the projected peak hours comprise an estimate of the CP hours and are identified prior to the optimization period.

14. The method of claim 11 , wherein the peak hours mask comprises a vector of binary values, each of the binary values corresponding to an hour of the optimization period and indicating whether the corresponding hour is a projected peak hour.

15. The method of claim 11 , further comprising:

predicting regional demand peaks for a geographic region in which the building is located;

defining the projected peak hours based on the predicted regional demand peaks; and

creating the peak hours mask using the projected peak hours.

16. The method of claim 15 , wherein the regional demand peaks are predicted based on at least one of load history data and weather data for the geographic region in which the building is located.

17. The method of claim 11 , wherein the PLC term comprises a rate factor defining a cost per unit of the electrical energy purchased from the utility during the CP hours;

the method further comprising:

identifying a geographic region in which the building is located; and

calculating the rate factor based on one or more parameters that depend on the identified geographic region.

18. An energy cost optimization system for a building, the system comprising:

HVAC equipment configured to consume one or more resources purchased from a utility or generated by a central plant for use in satisfying a building energy load; and

a controller configured to:

obtain a cost function comprising a peak load contribution (PLC) term, wherein the PLC term represents a cost based on an amount of the one or more resources purchased from the utility during coincidental peak (CP) hours of an optimization period comprising a plurality of time steps, the CP hours comprising a subset of the plurality of time steps in the optimization period, wherein the cost is a function of one or more decision variables representing an amount of the one or more resources to be consumed by the HVAC equipment during each of the plurality of time steps;

modify the cost function by applying a peak hours mask to the PLC term, wherein the peak hours mask identifies one or more hours in the optimization period as projected peak hours and causes the controller to assign substantially zero cost, in the PLC term, to the one or more resources purchased from the utility during any hours not identified as projected peak hours; and

allocate, to each of the time steps within the optimization period, an amount of the one or more resources to be consumed by the HVAC equipment during the time step by performing an optimization process of the modified cost function to determine values of the decision variables.

19. The energy cost optimization system of claim 18 , wherein the peak hours mask comprises a vector of binary values, each of the binary values corresponding to an hour of the optimization period and indicating whether the corresponding hour is a projected peak hour.

20. The energy cost optimization system of claim 18 , wherein:

the PLC term comprises a rate factor defining a cost per unit of the electrical energy purchased from the utility during the CP hours; and

the controller is configured to:

identify a geographic region in which the building is located; and

calculate the rate factor based on one or more parameters that depend on the identified geographic region.

Assignments (3)

Continuity (2)

Cited By (10)

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