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Solar irradiance forecasting using ground-based sky images
SIOG 236
06/07/2018
Cristian Cortes A.
1
Contents
• Motivation
• Sky cameras
• Data Processing
• Limitations
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Motivation• Why we need forecast?
• Electricity generated from solar energy is related with weather conditions (variability)
• Higher levels of solar power on the electric grid can be problematic (curtailment)
[R. Escobar, 2016]
[ T. Stoffel & S. Wilcox, 2004]3
Samples of sky images
[Kleissl, 2013]4TSI USI
Sky cameras available
Name Developer Image formatCommercially
available
TSI-800 YES JPG ???
USI UCSD PNG Yes
SW-02 All sky imager Steady-Sun JPG Yes
ASI-16 All Sky Imager Eko Instruments HDR JPG Yes
[Chow et al., 2011] [steadysun] [Chow et al., 2015] [EKO] 5
• Developed specifically for solar forecasting
• High Dynamic Range images
• Shadowband is not necessary
Fisheye LensSigma 4.5mm
Microprocessor Arduino MEGA 2560
with data acquisition breakout board
ComputerDual core 1.8 Ghz Intel
Atom, 4GB RAM
GPS
Harddrive MountFor removable hard drive
IMU
Power Distribution Board24, 12, & 5 VDC
Power Supply120 VAC in, 24VDC out
Camera Heatsink
High Current MOSFETsfor duty cycling coolers/heaters
CameraAllied Vision GE 2040C
UCSD Sky Imager (USI)
[Chow et al., 2015]6
Sky Imager Forecast Procedure
Calibrated Imagery
Detect Cloud
Ray trace shadows
Data of power or
irradiance
Determine cloud
attenuation
Power Forecast
Compute MotionForecast future
position
Cloud Base Height
Data
[Chow et al., 2015]7
Data processing
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2017-12-22 17:01:30 UTC
Red Channel
Blue Channel
Red - Blue ratio
Clear sky images for a whole day were processed
A Clear Sky Library is built
=
-Clear Sky Library
Cloud Decision
0: clear sky1: thin cloud2: thick cloud
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Preliminary Results
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Sky Imager
ray tracing of
direct solar beam
cloudmap
forecast domain
cloudmap legend
cloudclear sky
Cloud Decision
Projection
[Chow et al., 2015]
Deployment
11
𝜖ℎ =1
𝑛
𝑖=1
𝑛
(𝑠1𝑖 − 𝑠2
𝑖 )2
Estimating Cloud Base Height (CBH)
[Nguyen and Kleissl, 2014]
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Final Results
[Kleissl, 2013]13
Limitations
• Solar region issues
• Estimating cloud base height is not easy
• Clouds behavior• Shape is not constant
• More than one layer of clouds
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References
• Chow, C. W., Urquhart, B., Lave, M., Dominguez, A., Kleissl, J., Shields, J., & Washom, B. (2011). Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed. Solar Energy, 85(11), 2881–2893.
• Chow, C., Gohari, S., Urquhart, B., Yang, H., Kurtz, B., Nguyen, D., Ghonima, M., Mejia F., and Kleissl, J. (2015). Design and application of a high dynamic range sky imaging system for solar forecasting.
• Escobar, R. (2016). Fraunhofer Chile Seminar: Pronóstico de Irradiación y Producción en Plantas Solares
• Kleissl, J. (2013). Solar Energy Forecasting and Resource Assessment.
• Nguyen, D., & Kleissl, J. (2014). Stereographic methods for cloud base height determination using two sky imagers. Solar Energy, 107, 495–509.
• Stoffel, T. and Wilcox, S. (2004). Solar Radiation Measurement: A Workshop For The National Association of States Universities and Land Grant Colleges
• Urquhart, B., Kurtz, B., Dahlin, E., Ghonima, M., Shields, J. E., & Kleissl, J. (2015). Development of a sky imaging system for short-term solar power forecasting. Atmospheric Measurement Techniques, 8(2), 875–890.
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Solar irradiance forecasting using ground-based sky
images
SIOG 236
06/06/2018
Cristian Cortes A.
16