Distributed energy neural network integration system

• US 6,925,361 B1
• Filed: 10/28/2000
• Issued: 08/02/2005
• Est. Priority Date: 11/30/1999
• Status: Expired due to Fees

• Current Assignee: Orion Engineering Corporation
• Original Assignee: Orion Engineering Corporation
• Inventors: Sinnock, Herbert James
• Primary Examiner(s): Von Buhr, Maria N.
• Application Number:
  US09/699,296
• Time in Patent Office: 1,739 Days
• Field of Search: 700/22, 700 28- 37, 700286-290, 700/297, 700/298
• US Class Current: 700/286
• CPC Class Codes: G06N 3/043 based on fuzzy logic, fuzzy membership or fuzzy inference, e.g. adaptive neuro-fuzzy inference systems [ANFIS]

Abstract

A system that couples distributed power generators together as a collective unit for the purposes of selling or purchasing energy from the electrical power grid. The apparatus includes a charge/discharge controller and an adaptive controller. The charge/discharge controller transfers energy generated by the plurality of distributed power generators to the power grid. The adaptive controller directs when the charge/discharge controller transfers energy generated by at least one of the plurality of distributed power generators to the electrical grid.

Claims

1. An apparatus operably coupled to an electrical power grid and including a distributed power generator, the apparatus comprising:

a charge/discharge controller capable of transferring energy generated by the distributed power generator to the power grid and capable of transferring energy from the power grid to the apparatus, and

an adaptive controller that directs, based upon a correlation between at least one selected parameter and a profile, whether the charge/discharge controller transfers energy generated by the distributed power generator to the electrical power grid or from the power grid to the apparatus.

2. The apparatus according to claim 1, further including a neighborhood c controller having the charge/discharge controller housed therein, wherein the neighborhood controller interfaces with the power grid.

3. The apparatus according to claim 2, wherein the neighborhood controller provides the combined energy generating capacity of the plurality of distributed power generators to the power grid.

4. The apparatus according to claim 2, wherein the neighborhood controller enables bulk energy transactions between the plurality of distributed power generators and the power grid.

5. The apparatus according to claim 4, wherein the neighborhood controller provides blocks of energy that enable transactions on the wholesale electricity market.

6. The apparatus according to claim 1, wherein the distributed power generator is located proximal to an energy user.

7. The apparatus according to claim 1, wherein the charge/discharge controller includes circuitry for transferring energy from the power grid to an energy user located proximal to the distributed power generator based upon the least one selected parameter.

8. The apparatus according to claim 1, wherein the charge/discharge controller includes circuitry for transferring energy from the distributed power generator to an energy user.

9. The apparatus according to claim 1, further including an energy storage device and wherein the charge/discharge controller includes circuitry for transferring energy generated by the distributed power generator to the energy storage device.

10. The apparatus according to claim 9, wherein the adaptive controller directs the charge/discharge controller to transfer energy to the storage device based upon the at least one selected parameter.

11. The apparatus according to claim 2, wherein the neighborhood controller includes an energy storage device.

12. The apparatus according to claim 1, wherein the charge/discharge controller includes circuitry for transferring energy between an energy storage device and the power grid.

13. The apparatus according to claim 1, wherein the charge/discharge controller includes circuitry for transferring energy from an energy storage device to an energy user.

14. The apparatus according to claim 1, wherein the adaptive controller directs the charge/discharge controller based upon a parameter selected from the group consisting of:

energy price, energy load, current weather, and available energy.

15. The apparatus according to claim 1, wherein the adaptive controller includes a neural network for directing the charge/discharge controller to transfer energy to the electrical grid.

16. The apparatus according to claim 15 wherein the neural network includes a pattern database for storage and retrieval of profiles based upon measured parameters.

17. The apparatus according to claim 16 wherein the stored parameters are selected from the group consisting of:

energy load, current weather, available energy, and energy price.

18. The apparatus according to claim 16 wherein the neural network includes a pattern recognizer for correlating a current measured parameter with a selected profile from the pattern database.

19. The apparatus according to claim 18 wherein the neural network includes a control law generator for directing the charge/discharge controller based upon the correlation between the current measured parameter and the selected profile.

20. The apparatus according to claim 15, wherein the neural network includes a processor executing a set of instructions that instruct the charge/discharge controller to transfer energy to the power grid based upon a price of electricity on the grid and based upon a cost of generating electricity at the distributed power generator.

21. An apparatus operably coupled to an electrical power grid and including a distributed power generator, the apparatus comprising:

a charge/discharge controller capable of transferring energy

generated by the distributed power generator to the power grid and capable of

transferring energy from the power grid to the apparatus, and

an adaptive controller, including a neural network, that directs, the charge/discharge

controller to transfer energy generated by the distributed power generator to the

power grid or to transfer energy from the power grid to the apparatus.

22. The apparatus according to claim 21, further including an energy storage device and wherein the charge/discharge controller transfers to and retrieves energy from the energy storage device.

23. The apparatus according to claim 22, wherein the adaptive controller directs the charge/discharge controller to transfer energy to the storage device based upon the at least one selected parameter.

24. The apparatus according to claim 21, wherein the adaptive controller directs the charge/discharge controller based upon a parameter selected from the list consisting of:

energy price, energy load, current weather, and available energy.

25. The apparatus according to claim 21, wherein the neural network includes a pattern database for storage an retrieval of profiles based upon measured parameters.

26. The apparatus according to claim 25, wherein the stored parameters are selected from the group consisting of:

energy load, current weather, available energy, and energy price.

27. The apparatus according to claim 25, wherein the neural network includes a pattern recognizer for correlating a current measured parameter with a selected profile from the pattern database.

28. The apparatus according to claim 27, wherein the neural network includes a control law generator for directing the charge/discharge controller based upon the correlation between the current measured parameter and the selected profile.

29. The apparatus according to claim 21, wherein the neural network includes a processor executing a set of instructions that instruct the charge/discharge controller to transfer energy to the power grid based upon a price of electricity on the grid and based upon a cost of generating electricity at the distributed power generator.

30. A method for coupling an apparatus including a distributed power genrator to an electrical power grid, comprising:

determining, based upon a correlation between at least one selected parameter and a profile, whether to transfer energy from the distributed power generator to the electrical grid or to transfer energy from the electrical grid to the apparatus, and

selectively transferring energy from the distributed power generator to the electrical grid or form the electrical grid to the apparatus through a charge/discharge controller in response to the determining step.

31. The method according to claim 30, further comprising the step of determining, based upon at least one elected parameter, whether to transfer energy from the electrical grid to an energy storage device through the charge/discharge controller.

32. The method according to claim 30, further comprising the step of determining, based upon at least one selected parameter, whether to transfer energy from the electrical grid to an energy user through the charge/discharge controller.

33. The method according to claim 30, further comprising the step of determining, based upon at least one selected parameter, whether to transfer energy from the distributed power generator to an energy storage device through the charge/discharge controller.

34. The method according to claim 30, further comprising the step of determining, based upon at least one selected parameter, whether to transfer energy from the distributed power generator to an energy user through the charge/discharge controller.

35. The method according to claim 30, further comprising the step of determining, based upon at least one selected parameter, whether to transfer energy from an energy storage device to an energy user through the charge/discharge controller.

36. The method according to claim 30, further comprising the step of measuring the current value of the at least one selected parameter.

37. The method according to claim 36, further including the step of correlating the measured parameter the profile.

38. The method according to claim 37, wherein the step of correlating the measured parameter with the profile further includes the step of optimizing the operation of the charge/discharge controller using nonlinear algorithms.

39. The method according to claim 37, wherein the profile is stored in a pattern database.

40. The method according to claim 37, wherein the adaptive controller directs the charge/discharge controller based upon the correlation between the measured parameter and the profile.

41. The method according to claim 30, wherein the charge/discharge controller is housed within a neighborhood controller that interfaces with the power grid.

42. The method according to claim 41, wherein the neighborhood controller provides the combined energy generating capacity of the plurality of distributed power generators to the power grid.

43. The method according to claim 30, wherein the at least one selected parameter is selected from the group consisting of:

energy price, energy load, current weather, and available energy.