DISTRIBUTED SOLAR ENERGY PREDICTION IMAGING

• US 20180136366A1
• Filed: 05/27/2016
• Published: 05/17/2018
• Est. Priority Date: 05/29/2015
• Status: Abandoned Application

• Current Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Original Assignee: Board of Regents of the University of Texas System (University of Texas System)
• Inventors: VEGA-AVILA, ROLANDO E., RICHARDSON, Jr., WALTER B., KRISHNASWAMI, HARIHARAN, CERVANTES, MICHAEL
• Application Number:
  US15/577,441
• Publication Number:
  US 20180136366A1
• Time in Patent Office: Days
• CPC Class Codes: F24S 2020/16 Preventing shading effects
• CPC Class Codes: F24S 2201/00 Prediction; Simulation
• CPC Class Codes: G01W 1/00 Meteorology
• CPC Class Codes: G01W 1/10 Devices for predicting weather conditions computers per se G06; display devices G09
• CPC Class Codes: G01W 1/12 Sunshine duration recorders measuring intensity of sunshine G01J
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06T 11/60 Editing figures and text; Combining figures or text
• CPC Class Codes: G06T 2207/30192 Weather; Meteorology
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: H02S 40/00 Components or accessories in combination with PV modules, not provided for in groups H02S10/00 - H02S30/00
• CPC Class Codes: H02S 99/00 Subject matter not provided for in other groups of this subclass
• CPC Class Codes: Y02E 10/50 Photovoltaic [PV] energy

Abstract

Concepts of distributed solar energy prediction imaging are described. In one embodiment, a solar forecast system includes a computing environment, a network, and an imaging device. Among other elements, the imaging device can include a wide-angle optical component, an imaging assembly, and a computing device. The computing device of the imaging device can capture an array of images using the imaging assembly, combine the array of images into a combined-resolution image, transform the combined-resolution image into a transformed image based on a calibration transformation matrix associated with the wide-angle optical component, identify and track cloud features in the transformed image, and generate a solar forecast using ray tracing based on the cloud features. The imaging device can also transmit the solar forecast to the computing environment via the network, and the computing environment can fuse solar forecast data from several imaging device into a distributed geographic area forecast.

Claims

1. A solar forecast system, comprising:

a computing environment;

a network; and

an imaging device communicatively coupled to the computing environment via the network, the imaging device comprising an imaging assembly and a computing device, the computing device being configured to;

capture an array of images using the imaging assembly;

combine the array of images into a combined-detail image;

identify and track cloud features in the combined-detail image;

generate a solar forecast using ray tracing based on the cloud features in the combined-detail image; and

transmit the solar forecast to the computing environment via the network.

2. The solar forecast system according to claim 1, wherein the computing device of the imaging device is further configured to tone map the array of images to combine the array of images into the combined-detail image.

3. The solar forecast system according to claim 1, wherein:

the imaging assembly comprises a wide-angle optical component to capture a wide view of sky in the array of images; and

the computing device of the imaging device is further configured to transform the combined-detail image into a transformed image based on a calibration transformation matrix associated with the wide-angle optical component.

4. The solar forecast system according to claim 1, wherein:

the imaging device comprises a plurality of imaging devices; and

each of the plurality of imaging devices transmits a respective solar forecast to the computing environment via the network.

5. The solar forecast system according to claim 4, wherein the plurality of imaging devices comprise a distributed geographical network of solar forecast imaging devices.

6. The solar forecast system according to claim 4, wherein the computing environment is configured to combine the respective solar forecast from each of the plurality of imaging devices into a distributed geographic area solar forecast.

7. The solar forecast system according to claim 4, wherein the computing environment is configured to combine cloud height and horizontal projection data among the respective solar forecast from each of the plurality of imaging devices.

8. A solar forecast method, comprising:

capturing, by a computing device, an array of images using an imaging assembly;

combining, by the computing device, the array of images into a combined-detail image;

transforming, by the computing device, the combined-detail image into a transformed image; and

tracking, by the computing device, cloud features in the transformed image.

9. The solar forecast method according to claim 8, wherein combining the array of images further comprises tone mapping the array of images.

10. The solar forecast method according to claim 8, wherein:

the imaging assembly comprises a wide-angle optical component to capture a wide view of sky in the array of images; and

transforming the combined-detail image comprises transforming, by the computing device, the combined-detail image into the transformed image based on a calibration transformation matrix associated with the wide-angle optical component.

11. The solar forecast method according to claim 8, further comprising generating, by the computing device, a solar forecast using the transformed image and based on the cloud features.

12. The solar forecast method according to claim 11, wherein:

the transformed image comprises one of a plurality of transformed images captured over a distributed geographic area; and

the method further comprises fusing, by the computing device, the plurality of transformed images to generate a distributed geographic area solar forecast.

13. The solar forecast method according to claim 12, wherein the fusing comprises combining, by the computing device, cloud height and horizontal projection data from the plurality of transformed images.

14. An imaging device, comprising:

a computing device; and

an imaging assembly comprising a wide-angle optical component, the computing device being configured to;

capture an array of images using the imaging assembly;

combine the array of images into a combined-detail image; and

transform the combined-detail image into a transformed image based on a calibration transformation matrix associated with the wide-angle optical component.

15. The imaging device according to claim 14, wherein the computing device is further configured to tone map the array of images to combine the array of images into the combined-detail image.

16. The imaging device according to claim 14, wherein the computing device is further configured to identify and track cloud features in the transformed image.

17. The imaging device according to claim 16, wherein the computing device is further configured to generate a solar forecast using ray tracing based on the cloud features in the transformed image.

18. The imaging device according to claim 17, wherein the computing device is further configured to transmit the solar forecast to a computing environment via a network.

19. The imaging device according to claim 18, wherein the computing environment receives a plurality of solar forecasts from a plurality of imaging devices in a distributed geographical network of imaging devices.

20. The imaging device according to claim 19, wherein the computing environment is configured to combine the plurality of solar forecasts into a distributed geographic area solar forecast.