Development of a sky imaging system for short-term solar power forecasting

Atmospheric Measurement Techniques

Volumn 8, Issue 2, 2015, Pages 875-890

  Urquhart, B ^a   Kurtz, B ^a   Dahlin, E ^a   Ghonima, M ^a   Shields, J E ^a   Kleissl, J ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; NOISE; RADIOMETRIC SURVEY; REMOTE SENSING; SOLAR POWER; VISIBILITY; WAVELENGTH;

UNITED STATES;

EID: 84923325337     PISSN: 18671381     EISSN: 18678548     Source Type: Journal    
DOI: 10.5194/amt-8-875-2015     Document Type: Article

References (43)

1. Anderson, M.: Studies of the woodland climate: I. The photographic computation of light conditions, J. Ecol., 52, 27-41, doi:10.2307/2257780, 1964.
2. Bayer, B. E.: Color Filter Array, U.S. Patent No. 3,971,065, U.S. Patent and Trademark Office, Washington, DC, 1975.
3. Brown, H. E.: The canopy camera, Station Paper 72, Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1962.
4. Cazorla, A., Olmo, F. J., and Alados-Arboledas, L.: Development of a sky imager for cloud cover assessment, J. Opt. Soc. Am., 25, 29-39, doi:10.1364/JOSAA.25.000029, 2008.
5. Chow, C. W., Urquhart, B., Lave, M., Dominguez, A., Kleissl, J., Shields, J. E., andWashom, B.: Intra-hour forecasting with a total s ky imager at the UC San Diego solar energy testbed, J. Sol. Energ., 85, 2881-2893, doi:10.1016/j.solener.2011.08.025, 2011.
6. Debevec, P. and Malik, J.: Recovering high dynamic range radiance maps from pho tographs, Proceedings of the ACM SIGGRAPH'97, Los Angeles CA, 369-378, 1997.
7. Dupree, W., Morse, D., Chan, M., Tao, X., Iskenderian, H., Reiche, C.,Wolfson, M., Pinto, J.,Williams, J. K., Albo, D., Dettling, S., Steiner, M., Benjamin, S., and Weygandt, S.: The 2008 CoSPA forecast demonstration (collaborative storm prediction for aviation), Proceedings of the 89th Meeting of the American Meteorological Society, Special Sympo sium on Weather-Air Traffic, Phoenix, AZ, 2009.
8. Dye, D.: Looking skyward to study ecosystem dynamics, Eos T. Am. Geophys. Un., 93, 141-143 doi:10.1029/2012EO140002, 2012.
9. Fauguera s, O: Three-dimensional Computer Vision, MIT Press, Cambridge, ISBN 0-262-06158-9, 1993.
10. Feister, U. Shields, J. E.: Cloud and radiance measurements with the VIS/NIR Daylight Whole Sky Imager at Lindenberg (Germany), Meteorol. Z., 14, 627-639, doi:10.1127/0941-2948/2005/0066, 2005.
11. Fu, C. L. and Cheng, H. Y.: Predicting solar irradiance with allsky image features via regression, J. Sol. Energ., 97, 537-550, doi:10.1016/j.solener.2013.09.016, 2013.
12. Gohari, S. M. I., Urquhart, B., Yang, H., Kurtz, B., Nguyen, D., Chow C. W., Ghonima, M., and Kleissl, J.: Comparison of solar power output forecasting p erformance of the Total Sky Imager and the University of California, San Diego Sky Imager, Energy Procedia, 49, 2340-2350, doi:10.1016/j.egypro.2014.03.248, 2014.
13. Gonzales, Y., Lopez, C., and Cuevas, E.: Automatic observation of cloudiness: analysis of all-sky images, TECO-2012, WMO Technical Conference on Meteorological and Environmental Instruments and Methods of Observation, Brussels, Belgium, 16-18 October 2012.
14. Hartley, R. and Zisserman, A.: Multiple view geometry in computer vision, Cambridge University Press, ISBN: 9780511811685, doi:10.1017/CBO9780511811685, 2004.
15. Hill, R.: A lens for whole sky photogra phs, Q. J. Roy. Meteorol. Soc., 50, 227-235, doi:10.1002/qj.49705021110, 1924.
16. Huo, J. and Lu, D.: Comparison of cloud cover from all-sky imager and meteorological observer, J. Atmos. Ocean. Tech., 29, 1093-1101, doi:10.1175/JTECH-D-11-00006.1, 2012.
17. Johnson, R. W., Koehler, T. L., and Shields, J. E.: A Multi-Station Set of Whole Sky Imagers and A Preliminary Assessment of the Emerging Data Base, Pro ceedings of the Cloud Impacts on DOD Operations and Systems-1988 Workshop, 159-162, 1988.
18. Johnson, R. W., Hering, W. S., and Shields, J. E.: Automated Visibility and Cloud Cover Measurements with a Solid-State Imag ing System, University of California, San Diego, Scripps Institution of Oceanography, Marine Physical Laboratory, SIO Ref. 89-7, GL-TR-89-0061, NTIS No. ADA216906, 1989.
19. Kalisch, J. and Macke, A.: Estimation of th e total cloud cover with high temporal resolution and parametrization of short-term fluctuations of sea surface insolation, Meteorol. Z., 17, 603-611, doi:10.1127/0941-2948/2008/0321, 2008.
20. Klebe, D. I., Blatherwick , R. D., and Morris, V. R.: Ground-based all-sky mid-infrared and visible imagery for purposes of characterizing cloud properties, Atmos. Meas. Tech., 7, 637-645, doi:10.5194/amt-7-637-2014, 2014.
21. Long, C. N.,DeLuisi, J. J.: Development of an automated hemispheric sky imager for cloud fraction retrievals, Proceedings of the 10th Symposium on Meteorological Observations and Instrumentation, Phoenix, Arizona, American Meteorological Societ y 171-174 1998.
22. Long, C. N., Sabburg, J. M., Calbó, J., and Pagés, D.: Retrieving cloud characteristics from ground-based daytime color all-sky images, J. Atmos. Ocean. Technol., 23, 633-652, doi:10.1175/JTECH1875.1, 2006.
23. Mann, S. and Picard, R. W.: On being "undigital " with digital cameras: extending dynamic range by combining differently exposed pictures, Technical Report 323, MIT Media Lab Perceptual Computing Section, 1994 (also in: Proceedings of Imaging Science and Technology 48th annual conference, 422-428, 1995).
24. Marquez, R. and Coimbra, C. F. M.: Intra-hour DNI forecasting methodology based on cloud tracking image analysis, J. Sol. Energ., 91, 327-336, doi:10.1016/j.solener.2012.09.018, 2013.
25. Mathiesen, P. and Kleissl, J.: Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States, J. Sol. Energ., 85, 967-977, doi:10.1016/j.solener.2011.02.013, 2011.
26. Mathiesen, P., Collier, C., and Kleissl, J.: A high-resolution cloud-Assimilating numerical weather prediction model for solar irradiance forecasting, J. Sol. Energ., 92, 47-61, doi:10.1016/j.solener.2013.02.018, 2013.
27. Miyamoto, K.: Fish Eye Lens, J. Opt. Soc. Am., 54, 1060-1061, doi:10.1364/JOSA.54.001060, 1964.
28. Nakajima, T., Tonna, G., Rao, R., Boi, P., Kaufman, Y., and Holben, B.: Use of sky brightness measurements from ground for remote sensing of particulate polydispersions, J. Appl. Optics, 35, 2672-2686, doi:10.1364/AO.35.002672, 1996.
29. Perez, R., Cebecauer, T., and Súri, M.: Semi-empirical satellite models, chapter 2 in: Solar Energy Forecasting and Resource Assessment, edited by: Kleissl, J., Elsevier, ISBN: 978-0-12-397177-7, 2013.
30. Reda, I. and Andreas, A.: Solar posit ion algorithm for solar radiation applications, J. Sol. Energ., 76, 577-589, doi:10.1016/j.solener.2003.12.003, 2004.
31. Rogers, M., Miller, S., Combs, C., Benjamin, S., Alexander, C., Sengupta, M., Kleissl, J., and Mathiesen, P.: Validation and analysis of HRRR insolation forecasts using SURFRAD. Proceedings of the American Solar Energy Society, Rayleigh, NC, 2012.
32. Román, R., Antón, M., Cazorla, A., de Miguel, A., Olmo, F. J., Bilbao, J., and Alados-Arboledas, L.: Calibration of an all-sky camera for obtaining sky radiance at three wavelengths, Atmos. Meas. Tech., 5, 2013-2024, doi:10.5194/amt-5-2013-2012, 2012.
33. Sebag, J., Krabbendam, V. L., Claver, C. F., Andrew, J., Barr, J. D., and Klebe, D.: LSST IR camera for cloud monitoring and observation planning, Proceedings of the International Society of Photonics and Optics, Ground-ba sed and Airborne Telescopes II conference (SPIE 7012), 7012, doi:10.1117/12.789570, 2008.
34. Shields, J. E., Johnson, R. W., and Karr, M. E.: Automated Whole Sky Imagers for Continuous Day and Night Cloud Field Assessment, Proceedings of the Cloud Impacts on DOD Operations and Systems Conference, 1993 a.
35. Shields, J. E., Johnson, R.W., and Koehler, T. L.: Automated Whole Sky Imaging Systems for Cloud Field Assessment, Proceedings of the Fourth Symposium on Global Change Studies, American Meteorological Society, Boston, 17-22 January, 1993 b.
36. Shields, J. E., Johnson, R. W., Karr, M. E., and Wertz, J. L.: Automatic day/night whole sky imager for field a ssessment of cloud cover distributions and radiance distributions, Proceedings of the 10th Symposium on Meteorological Observations and Instrumentations, Phoenix, AZ, American Meteorological Society, Boston, 165-170, 1998 a.
37. Shiel ds, J. E., Karr, M. E., Tooman, T. P., Sowle, D. H., and Moore, S. T.: The Whole Sky Imager-A Year of Progress, Proceedings of Eighth Atmospheric Radiation Measurement (ARM)Science Team Meeting, 1998 b.
38. Shields, J. E., Karr, M. E., Johnson, R. W., and Burden, A. R.: Day/night whole sky imagers for 24-h cloud and sky assessment: history and overview, J. Appl. Optics, 52, 1605-1616, doi:10.1364/AO.52.001605, 2013.
39. Stumpfel, J., Tchou, C., Jones, A., Hawkins, T.,Wenger, A., and Debevec, P.: Direct HDR capture of the sun and sky, AFRIGRAPH 2004, 3rd International Conference on Computer Graphics, Virtual Reality, Visualization and Interaction in Africa, Cape Town, South Africa-3-5 November, doi:10.1145/1029949.1029977, 2004.
40. Urquhart, B., Ghonima, M., Nguyen, D., Kurtz, B., Chow, C. W., and Kleissl, J.: Sky imaging systems for short-term solar forecasting, chapter 9 in: Solar Energy Forecasting and Resource Assessment, edited by: Kleissl, J., Elsevier, ISBN: 978-0-12-397177-7, 2013.
41. Urquhart, B., Kurtz, B., and Kleissl, J.: Sky camera geometric calibration using solar observations, submitted, 2015.
42. Wood-Bradley P.,Zapata J.,Pye, J.: Cloud tracking with optical flow for short-term solar forecasting, Proceedings of the 50th Conference of the Australian Solar Energy Society, Melbourne, December 2012.
43. Yang, H., Kurtz, B., Nguyen, D., Urquhart, B., Chow, C. W., Ghonima, M., and Kleissl, J.: Solar irradiance forecasting using a ground-based sky imager developed at UC San Diego, J. Sol. Energ., 103, 503-524, doi:10.1016/j.solener.2014.02.044, 2014.