INCORPORATING A LOAD CHANGE PENALTY IN CENTRAL PLANT OPTIMIZATION

• US 20150316946A1
• Filed: 02/27/2015
• Published: 11/05/2015
• Est. Priority Date: 05/01/2014
• Status: Active Grant

• Current Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Original Assignee: Johnson Controls Technology Company (Johnson Controls International plc)
• Inventors: Wenzel, Michael J., Turney, Robert D.
• Granted Patent: US 10,101,730 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/418 Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G05B 2219/31414 Calculate amount of production energy, waste and toxic release
• CPC Class Codes: G05B 2219/32021 Energy management, balance and limit power to tools
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02P 70/10 Greenhouse gas [GHG] capture, material saving, heat recovery or other energy efficient measures, e.g. motor control, characterised by manufacturing processes, e.g. for rolling metal or metal working
• CPC Class Codes: Y02P 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• CPC Class Codes: Y02P 90/80 Management or planning
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving

Abstract

An optimization system for a central plant includes a processing circuit configured to receive load prediction data indicating building energy loads and utility rate data indicating a price of one or more resources consumed by equipment of the central plant to serve the building energy loads. The optimization system includes a high level optimization module configured to generate an objective function that expresses a total monetary cost of operating the central plant over the optimization period as a function of the utility rate data and an amount of the one or more resources consumed by multiple groups of the central plant equipment. The optimization system includes a load change penalty module configured to modify the objective function to account for a load change penalty resulting from a change in an amount of the building energy loads assigned to one or more of the groups of central plant equipment.

Claims

1. An optimization system for a central plant configured to serve building energy loads, the optimization system comprising:

a processing circuit configured to receive load prediction data indicating building energy loads for a plurality of time steps in an optimization period and utility rate data indicating a price of one or more resources consumed by equipment of the central plant to serve the building energy loads at each of the plurality of time steps;

a high level optimization module configured to generate an objective function that expresses a total monetary cost of operating the central plant over the optimization period as a function of the utility rate data and an amount of the one or more resources consumed by multiple groups of the central plant equipment at each of the plurality of time steps;

wherein the high level optimization module is configured to optimize the objective function over the optimization period subject to a set of constraints to determine an optimal amount of the building energy loads assigned to each of the groups of central plant equipment at each of the plurality of time steps; and

a load change penalty module configured to modify the objective function to account for a load change penalty resulting from a change in the amount of the building energy loads assigned to one or more of the groups of central plant equipment.

2. The optimization system of claim 1, wherein the high level optimization module uses linear programming to generate and optimize the objective function.

3. The optimization system of claim 1, wherein modifying the objective function to account for the load change penalty comprises:

adding one or more load change variables to the objective function, each of the load change variables representing a change in the energy load assigned to a corresponding group of the central plant equipment; and

weighting each of the load change variables with a cost representing a monetary penalty associated with a per unit change in the energy load assigned to the corresponding group of central plant equipment.

4. The optimization system of claim 1, wherein modifying the objective function to account for the load change penalty comprises:

adding one or more constraints to the set of constraints that require the change in the energy load assigned to a group of the central plant equipment to be less than or equal to a threshold value.

5. The optimization system of claim 4, wherein the threshold value is a percentage of a maximum capacity of the group of central plant equipment.

6. The optimization system of claim 1, wherein:

the objective function comprises a cost vector including cost variables that represent a monetary cost associated with each of the one or more resources consumed by the central plant equipment to serve the building energy loads at each of the plurality of time steps; and

modifying the objective function to account for the load change penalty comprises adding a load change cost to the cost vector.

7. The optimization system of claim 6, wherein modifying the objective function to account for the load change penalty comprises adding a load change cost to the cost vector for each of the groups of central plant equipment.

8. The optimization system of claim 1, wherein:

the objective function comprises a decision matrix including load variables that represent an energy load for each of the multiple groups of the central plant equipment at each of the plurality of time steps;

modifying the objective function to account for the load change penalty comprises adding a load change variable to the decision matrix; and

optimizing the objective function comprises determining optimal values for the variables in the decision matrix.

9. The optimization system of claim 8, wherein modifying the objective function to account for the load change penalty comprises adding a load change variable to the decision matrix for each of the groups of central plant equipment.

10. The optimization system of claim 8, wherein modifying the objective function to account for the load change penalty comprises adding one or more constraints on the load change variable to the set of constraints for each of the plurality of time steps in the optimization period;

wherein the constraints on the load change variable for each time step require the load change variable to be greater than or equal to a change in the energy load assigned to a corresponding group of central plant equipment relative to a previous time step.

11. A method for incorporating a load change penalty in an optimization process for a central plant, the method comprising:

receiving, at a processing circuit of a central plant optimization system, load prediction data indicating building energy loads for a plurality of time steps in an optimization period and utility rate data indicating a price of one or more resources consumed by equipment of the central plant to serve the building energy loads at each of the plurality of time steps;

generating, by a high level optimization module of the central plant optimization system, an objective function that expresses a total monetary cost of operating the central plant over the optimization period as a function of the utility rate data and an amount of the one or more resources consumed by multiple groups of the central plant equipment at each of the plurality of time steps;

optimizing, by the high level optimization module, the objective function over the optimization period subject to a set of constraints to determine an optimal amount of the building energy loads assigned to each of the groups of central plant equipment at each of the plurality of time steps; and

modifying, by a load change penalty module of the central plant optimization system, the objective function to account for a load change penalty resulting from a change in the amount of the building energy loads assigned to one or more of the groups of central plant equipment.

12. The method of claim 11, wherein the high level optimization module uses linear programming to generate and optimize the objective function.

13. The method of claim 11, wherein modifying the objective function to account for the load change penalty comprises:

adding one or more load change variables to the objective function, each of the load change variables representing a change in the energy load assigned to a corresponding group of the central plant equipment; and

weighting each of the load change variables with a cost representing a monetary penalty associated with a per unit change in the energy load assigned to the corresponding group of central plant equipment.

14. The method of claim 11, wherein modifying the objective function to account for the load change penalty comprises:

adding one or more constraints to the set of constraints that require the change in the energy load assigned to a group of the central plant equipment to be less than or equal to a threshold value.

15. The method of claim 14, wherein the threshold value is a percentage of a maximum capacity of the group of central plant equipment.

16. The method of claim 11, wherein:

the objective function comprises a cost vector including cost variables that represent a monetary cost associated with each of the one or more resources consumed by the central plant equipment to serve the building energy loads at each of the plurality of time steps; and

modifying the objective function to account for the load change penalty comprises adding a load change cost to the cost vector.

17. The method of claim 16, wherein modifying the objective function to account for the load change penalty comprises adding a load change cost to the cost vector for each of the groups of central plant equipment.

18. The method of claim 11, wherein:

the objective function comprises a decision matrix including load variables that represent an energy load for each of the multiple groups of the central plant equipment at each of the plurality of time steps;

modifying the objective function to account for the load change penalty comprises adding a load change variable to the decision matrix; and

optimizing the objective function comprises determining optimal values for the variables in the decision matrix.

19. The method of claim 18, wherein modifying the objective function to account for the load change penalty comprises adding a load change variable to the decision matrix for each of the groups of central plant equipment.

20. The method of claim 18, wherein modifying the objective function to account for the load change penalty comprises adding one or more constraints on the load change variable to the set of constraints for each of the plurality of time steps in the optimization period;

wherein the constraints on the load change variable for each time step require the load change variable to be greater than or equal to a change in the energy load assigned to a corresponding group of central plant equipment relative to a previous time step.