Method and apparatus for managing an energy consuming load

• US 9,110,647 B2
• Filed: 05/14/2013
• Issued: 08/18/2015
• Est. Priority Date: 07/11/2006
• Status: Active Grant

• Current Assignee: Encycle Technologies, Inc.
• Original Assignee: Regen Energy Inc.
• Inventors: Kulyk, Roman, Kerbel, Mark
• Primary Examiner(s): JARRETT, RYAN A
• Application Number:
  US13/893,856
• Publication Number:
  US 20130268137A1
• Time in Patent Office: 826 Days
• Field of Search: 700/296
• US Class Current: 1/1
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 1/26 Power supply means, e.g. regulation thereof for memories G11C
• 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: H02J 13/00004 characterised by the power network being locally controlled
• CPC Class Codes: H02J 13/00026 involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• CPC Class Codes: Y04S 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 40/126 using wireless data transmission

Abstract

A method for managing an energy consuming load in a group of energy consuming loads and a method for managing the group of energy consuming loads. The method includes generating sets of load state data from the loads, making enablement state decisions for one or more loads using the sets of load state data, and implementing the enablement state decisions. Each of the enablement state decisions reflects an enablement state of a load, wherein the enablement state is either a load enabled state where the load is capable of operating even when the load is not actually operating or a load disabled state where the load is not capable of operating. A computer readable medium may include computer readable instructions for directing a processor to perform the methods and make the enablement state decision. Further, an apparatus comprised of a processor may be programmed to perform the methods.

Claims

1. A method for managing a group of energy consuming loads comprising a plurality of loads, the method comprising:

(a) generating a set of load state data from each of the loads in the group of loads, wherein each of the loads in the group of loads has an energy demand and wherein each of the loads in the group of loads has a duty cycle;

(b) making an enablement state decision for each of the loads using the sets of load state data from the loads, wherein each of the enablement state decisions reflects an enablement state of a corresponding load in the group of loads, wherein the enablement state is either a load enabled state or a load disabled state, wherein the load enabled state is a state where the corresponding load is capable of operating even when the corresponding load is not actually operating, wherein the load disabled state is a state where the corresponding load is not capable of operating, wherein the enablement state decisions are made with a goal of achieving a target system equilibrium for the group of loads and wherein the target system equilibrium is equal to a sum for all of the loads in the group of loads of a product of the energy demand of one of the loads and the duty cycle of the one of the loads; and

(c) implementing the enablement state decisions.

2. The method as claimed in claim 1 wherein each of the loads in the group of loads is an electrical load.

3. The method as claimed in claim 1 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle and wherein the enablement state decisions are constrained by the enablement needs of the loads.

4. The method as claimed in claim 1 wherein the enablement state decisions for the group of loads are made in a decision making sequence.

5. The method as claimed in claim 4 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle, and wherein the decision making sequence is dependent upon the enablement need of each of the loads.

6. The method as claimed in claim 4 wherein the decision making sequence is dependent upon the energy demand of each of the loads.

7. The method as claimed in claim 5 wherein the decision making sequence is further dependent upon the energy demand of each of the loads.

8. The method as claimed in claim 1, further comprising repeating (a), (b) and (c) in accordance with a schedule.

9. The method as claimed in claim 8 wherein the schedule is comprised of at least one period.

10. The method as claimed in claim 9 wherein the period is comprised of a plurality of segments.

11. The method as claimed in claim 10 wherein the enablement state decisions for the group of loads are made in a decision making sequence.

12. The method as claimed in claim 11 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle, wherein the decision making sequence is dependent upon the enablement need of each of the loads, and wherein the enablement need of each of the loads is defined by a remaining number of segments in the period during which the load must be in the load enabled state in order to achieve its duty cycle.

13. The method as claimed in claim 11 wherein the decision making sequence is dependent upon the energy demand of each of the loads.

14. The method as claimed in claim 12 wherein the decision making sequence is further dependent upon the energy demand of each of the loads.

15. The method as claimed in claim 1, further comprising assigning the duty cycle to each of the loads in the group of loads.

16. The method as claimed in claim 1 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle, and wherein each of the sets of load state data from the group of loads is comprised of an enablement need indication of the enablement need of the load and an energy demand indication of the energy demand of the load.

17. The method as claimed in claim 16 wherein each of the sets of load state data from the group of loads is further comprised of a duty cycle indication of the duty cycle of the load.

18. The method as claimed in claim 17 wherein the enablement state decision is constrained by the enablement need of the load.

19. The method as claimed in claim 17 wherein each of the sets of load state data from the group of loads is further comprised of a load identifying indication identifying the load and a time indication of a time to which the set of load state data relates.

20. The method as claimed in claim 1 wherein the duty cycle for each of the loads is an assigned duty cycle which represents a percentage of time that the load is in the load enabled state, wherein at least one of the loads is a discretionary load, wherein the at least one discretionary load is configured to operate according to a natural duty cycle which represents a percentage of time that the at least one discretionary load must actually operate in order to provide a particular result, and wherein the operation of the at least one discretionary load according to the natural duty cycle is constrained by the assigned duty cycle for the at least one discretionary load.

21. The method as claimed in claim 20 wherein the natural duty cycle for the at least one discretionary load is less than 100 percent.

22. The method as claimed in claim 1 wherein at least one of the loads in the group of loads is comprised of a discretionary load, and wherein the duty cycle for at east one of the discretionary loads is less than 100 percent.

23. A method for managing an energy consuming load in a group of energy consuming loads comprising the load and a plurality of other loads, the method comprising:

(a) generating a set of load state data from the load, wherein each of the loads in the group of loads has an energy demand and wherein each of the loads in the group of loads has a duty cycle;

(b) compiling the set of load state data generated from the load with sets of load state data generated from the other loads;

(c) making an enablement state decision for the load using the compiled sets of load state data, wherein the enablement state decision reflects an enablement state of the load, wherein the enablement state is either a load enabled state or a load disabled state, wherein the load enabled state is a state where the load is capable of operating even when the load is not actually operating, and wherein the load disabled state is a state where the load is not capable of operating, wherein the enablement state decision is made with a goal of achieving a target system equilibrium for the group of loads and wherein the target system equilibrium is equal to a sum for all of the loads in the group of loads of a product of the energy demand of one of the loads and the duty cycle of the one of the loads; and

(d) implementing the enablement state decision for the load.

24. The method as claimed in claim 23 wherein each of the loads in the group of loads is an electrical load.

25. The method as claimed in claim 23 wherein the load has an enable need in order to achieve its duty cycle and wherein the enablement state decision is constrained by the enablement need of the load.

26. The method as claimed in claim 23 wherein the enablement state decisions for the group of loads are made in a decision making sequence.

27. The method as claimed in claim 26 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle and wherein the decision making sequence is dependent upon the enablement need of each of the loads.

28. The method as claimed in claim 26 wherein the decision making sequence is further dependent upon the energy demand of each of the loads.

29. The method as claimed in claim 27 wherein the decision making sequence is further dependent upon the energy demand of each of the loads.

30. The method as claimed in claim 23, further comprising repeating (a), (b), (c) and (d) in accordance with a schedule.

31. The method as claimed in claim 30 wherein the schedule is comprised of at least one period.

32. The method as claimed in claim 31 wherein the period is comprised of a plurality of segments.

33. The method as claimed in claim 32 wherein the enablement state decisions for the group of loads are made in a decision making sequence.

34. The method as claimed in claim 33 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle, wherein the decision making sequence is dependent upon the enablement need of each of the loads, and wherein the enablement need of each of the loads is defined by a remaining number of segments in the period during which the load must be in the load enabled state in order to achieve its duty cycle.

35. The method as claimed in claim 23, further comprising assigning the duty cycle to the load.

36. The method as claimed in claim 23 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle, and wherein each of the sets of load state data from the group of loads is comprised of an enablement need indication of the enablement need of the load and an energy demand indication of the energy demand of the load.

37. The method as claimed in claim 36 wherein each of the sets of load state data from the group of loads is further comprised of a duty cycle indication of the duty cycle of the load.

38. The method as claimed in claim 37 wherein the enablement state decision is constrained by the enablement need of the load.

39. The method as claimed in claim 37 wherein each of the sets of load state data from the group of loads is further comprised of a load identifying indication identifying the load and a time indication of a time to which the set of load state data relates.

40. The method as claimed in claim 23 wherein the duty cycle for the load is an assigned duty cycle which represents a percentage of time that the load is in the load enabled state, wherein the load is configured to operate according to a natural duty cycle which represents a percentage of time that the load must actually operate in order to provide a particular result, and wherein the operation of the load according to the natural duty cycle is constrained by the assigned duty cycle for the load.

41. The method as claimed in claim 40 wherein the natural duty cycle for the load is less than 100 percent.

42. The method as claimed in claim 23 wherein the load is comprised of a discretionary load, and wherein the duty cycle for the load is less than 100 percent.

43. A non-transitory computer readable medium providing computer readable instructions for directing a processor to make an enablement state decision reflecting an enablement state of an energy consuming load in a group of energy consuming loads comprising the load and a plurality of other loads, wherein the enablement state is either a load enabled state or a load disabled state, wherein the load enabled state is a state where the load is capable of operating even when the load is not actually operating, and wherein the load disabled state is a state where the load is not capable of operating, the instructions comprising:

(a) generating a set of load state data from the load;

(b) compiling the set of load state data from the load with sets of load state data from the other loads; and

(c) processing the compiled sets of load state data in order to make the enablement state decision and making the enablement state decision with a goal of achieving a target system equilibrium for the group of loads, wherein each of the loads in the group of loads has an energy demand, wherein each of the loads in the group of loads has a duty cycle, and wherein the target system equilibrium is equal to a sum for all of the loads in the group of loads of a product of the energy demand of one of the loads and the duty cycle of the one of the loads.

44. The non-transitory computer readable medium as claimed in claim 43 wherein the load has an enablement need in order to achieve its duty cycle and wherein the enablement state decision is constrained by the enablement need of the load.

45. The non-transitory computer readable medium as claimed in claim 44 wherein the instructions are further comprised of directing a controller to implement the enablement state decision for the load.

46. The non-transitory computer readable medium as claimed in claim 43 wherein the enablement state decision is made in accordance with a schedule, wherein the schedule is comprised of at least one period, wherein the period is comprised of a plurality of segments, wherein the load has an enablement need in order to achieve its duty cycle, wherein the enablement need of the load is defined by a remaining number of segments in the period during which the load must be in the load enabled state in order to achieve its duty cycle, and wherein the enablement state decision is constrained by the enablement need of the load.

47. The non-transitory computer readable medium as claimed in claim 43 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle and wherein each of the sets of load state data from the group of loads is comprised of an energy demand indication of the energy demand of the load, a duty cycle indication of the duty cycle of the load and an enablement need indication of the enablement need of the load.

48. The non-transitory computer readable medium as claimed in claim 47 wherein the enablement state decision is constrained by the enablement need of the load.

49. The non-transitory computer readable medium as claimed in claim 47 wherein each of the sets of load state data from the group of loads is further comprised of a load identifying indication identifying the load and a time indication of a time to which the set of load state data relates.

50. An apparatus for making an enablement state decision reflecting an enablement state of an energy consuming load in a group of energy consuming loads comprising the load and a plurality of other loads, wherein the enablement state is either a load enabled state or a load disabled state, wherein the load enabled state is a state where the load is capable of operating even when the load is not actually operating, and wherein the load disabled state is a state where the load is not capable of operating, the apparatus comprising a processor programmed to:

(a) generate a. set of load state data from the load;

(b) compile the set of load state data from the load with sets of load state data from the other loads; and

(c) process the compiled sets of load state data in order to make the enablement state decision, wherein the processor is programmed to make the enablement state decision with a goal of achieving a target system equilibrium for the group of loads, wherein each of the loads in the group of loads has an energy demand, wherein each of the loads in the group of loads has a duty cycle, and wherein the target system equilibrium is equal to a sum for all of the loads in the group of loads of a product of the energy demand of one of the loads and the duty cycle of the one of the loads.

51. The apparatus as claimed in claim 50 wherein the load has an enablement need in order to achieve its duty cycle and wherein the enablement state decision is constrained by the enablement need of the load.

52. The apparatus as claimed in claim 51 wherein the processor is programmed to direct a controller to implement the enablement state decision for the load.

53. The apparatus as claimed in claim 50 wherein the enablement state decision is made in accordance with a schedule, wherein the schedule is comprised of at least one period, wherein the period is comprised of a plurality of segments, wherein the load has an enablement need in order to achieve its duty cycle, wherein the enablement need of the load is defined by a remaining number of segments in the period during which the load must be in the load enabled state in order to achieve its duty cycle, and wherein the enablement state decision is constrained by the enablement need of the load.

54. The apparatus as claimed in claim 50 wherein each of the loads in the group of loads has an enablement need in order to achieve its duty cycle and wherein each of the sets of load state data from the group of loads is comprised of an energy demand indication of the energy demand of the load, a duty cycle indication of the duty cycle of the load and an enablement need indication of the enablement need of the load.

55. The apparatus as claimed in claim 54 wherein the enablement state decision is constrained by the enablement need of the load.

56. The apparatus as claimed in claim 54 wherein each of the sets of load state data from the group of loads is further comprised of a load identifying indication identifying the load and a time indication of a time to which the set of load state data relates.