PHOTOVOLTAIC SYSTEM WITH MANAGED OUTPUT

• US 20110084551A1
• Filed: 10/12/2009
• Published: 04/14/2011
• Est. Priority Date: 10/12/2009
• Status: Active Grant

• Current Assignee: Nextracker
• Original Assignee: Sunpower Corporation (Totalenergies Se)
• Inventors: Campbell, Matt, Johnson, Robert, Kimber, Adrianne, Lenox, Carl J. S.
• Granted Patent: US 9,257,847 B2
• Time in Patent Office: Days
• US Class Current: 307/24
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02S 40/34 comprising specially adapted electrical connection means to be structurally associated with the PV module, e.g. junction boxes
• CPC Class Codes: H02S 50/00 Monitoring or testing of PV systems, e.g. load balancing or fault identification
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers

Abstract

Photovoltaic systems with managed output and methods for managing variability of output from photovoltaic systems are described. A system includes a photovoltaic module configured to receive and convert solar energy to DC power. The system also includes a sensor configured to detect a future change in solar energy to be received by the photovoltaic module. The system further includes a power conditioning unit coupled with the photovoltaic module and the sensor.

Claims

1. A photovoltaic system with managed output, the system comprising:

a photovoltaic module configured to receive and convert solar energy to DC power;

a sensor configured to detect a future change in solar energy to be received by the photovoltaic module, the sensor comprising a portfolio of distributed photovoltaic systems or a pair of modules, each module positioned at a unique distance from the photovoltaic module; and

a power conditioning unit coupled with the photovoltaic module and the sensor, the power conditioning unit configured to condition DC power from the photovoltaic module and to modify power output from the power conditioning unit based on the future change in solar energy.

2. The photovoltaic system of claim 1, wherein the sensor is the portfolio of distributed photovoltaic systems, the portfolio of distributed photovoltaic systems comprising nearby residential or commercial, or both, photovoltaic systems from a predetermined geographic area.

3. The photovoltaic system of claim 1, wherein the sensor is the pair of modules, the pair of modules configured to provide a delta in energy detected by the pair of modules.

4. The photovoltaic system of claim 3, wherein the sensor further comprises one or more additional modules, each module positioned at a unique distance from the photovoltaic module.

5. The photovoltaic system of claim 1, wherein the sensor further comprises a network of insolation sensor modules arranged around the perimeter of the photovoltaic system.

6. The photovoltaic system of claim 1, wherein the sensor further comprises a network of still cameras or a combination of still and video cameras.

7. The photovoltaic system of claim 1, further comprising:

a secondary sensor coupled with the sensor, the secondary sensor selected from the group consisting of an anemometer, a wind vane, a satellite data source, and a temperature sensor.

8. The photovoltaic system of claim 1, further comprising:

a neural-network configured to compute a value for the future change in solar energy detected by the sensor.

9. The photovoltaic system of claim 1, wherein the power conditioning unit is an inverter, the inverter configured to invert, to AC power, DC power from the photovoltaic module, the inverter also configured to modify AC power output from the inverter based on the future change in solar energy.

10. A method for managing variability of output from a photovoltaic system, the method comprising:

detecting a future change in solar energy to be received by a photovoltaic module, the detecting performed by a sensor comprising a portfolio of distributed photovoltaic systems or a pair of modules, each module positioned at a unique distance from the photovoltaic module; and

outputting power, from the photovoltaic system, based on the future change in solar energy.

11. The method of claim 10, wherein detecting the future change in solar energy to be received by the photovoltaic module comprises detecting by the portfolio of distributed photovoltaic systems, the portfolio of distributed photovoltaic systems comprising nearby residential or commercial, or both, photovoltaic systems from a predetermined geographic area.

12. The method of claim 10, wherein detecting the future change in solar energy to be received by the photovoltaic module comprises detecting by the pair of modules, the pair of modules configured to provide a delta in energy detected by the pair of modules.

13. The method of claim 12, wherein the sensor further comprises one or more additional modules, each module positioned at a unique distance from the photovoltaic module.

14. The method of claim 10, wherein the sensor further comprises a network of insolation sensor modules arranged around the perimeter of the photovoltaic system.

15. The method of claim 10, wherein the sensor further comprises a network of still cameras or a combination of still and video cameras.

16. The method of claim 10, wherein detecting the future change in solar energy to be received by the photovoltaic module further comprises detecting by a secondary sensor coupled with the sensor, the secondary sensor selected from the group consisting of an anemometer, a wind vane, a satellite data source, and a temperature sensor.

17. The method of claim 10, wherein detecting the future change in solar energy to be received by the photovoltaic module further comprises computing, by a neural-network, a value for the future change in solar energy.

18. A machine-accessible storage medium having instructions stored thereon which cause a data processing system to perform a method for managing variability of output from a photovoltaic system, the method comprising:

detecting a future change in solar energy to be received by a photovoltaic module, the detecting performed by a sensor comprising a portfolio of distributed photovoltaic systems or a pair of modules, each module positioned at a unique distance from the photovoltaic module; and

outputting power, from the photovoltaic system, based on the future change in solar energy.

19. The machine-accessible storage medium of claim 18, wherein detecting the future change in solar energy to be received by the photovoltaic module comprises detecting by the portfolio of distributed photovoltaic systems, the portfolio of distributed photovoltaic systems comprising nearby residential or commercial, or both, photovoltaic systems from a predetermined geographic area.

20. The machine-accessible storage medium of claim 18, wherein detecting the future change in solar energy to be received by the photovoltaic module comprises detecting by the pair of modules, the pair of modules configured to provide a delta in energy detected by the pair of modules.

21. The machine-accessible storage medium of claim 20, wherein the sensor further comprises one or more additional modules, each module positioned at a unique distance from the photovoltaic module.

22. The machine-accessible storage medium of claim 18, wherein the sensor further comprises a network of insolation sensor modules arranged around the perimeter of the photovoltaic system.

23. The machine-accessible storage medium of claim 18, wherein the sensor further comprises a network of still cameras or a combination of still and video cameras.

24. The machine-accessible storage medium of claim 18, wherein detecting the future change in solar energy to be received by the photovoltaic module further comprises detecting by a secondary sensor coupled with the sensor, the secondary sensor selected from the group consisting of an anemometer, a wind vane, a satellite data source, and a temperature sensor.

25. The machine-accessible storage medium of claim 18, wherein detecting the future change in solar energy to be received by the photovoltaic module further comprises computing, by a neural-network, a value for the future change in solar energy.