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Copyright © 2016 Clean Power Research, L.L.Cv052814
Quantifying Uncertainty with Satellite-to-Ground Tuning
Adam KankiewiczSandia/EPRI 5th PV Performance Modeling Workshop
May 9th 2016
Copyright © 2016 Clean Power Research, L.L.C.
Presentation Outline
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Motivation
Ground data
Satellite irradiance modeling
How and why we tune satellite data
Tuning uncertainty
Key takeaways
Motivation: I Have X Amount of Ground Data. Can You Perform a (Viable) Tuning Study???
How does length or time period of ground data influence tuning study uncertainty?
GH
I (W
/m2 )
Ground-based Solar Resource Monitoring
Necessary to understand local variability effects
Ground truth for tuning process
Have to place into long term reference frame for proper resource context!
Image courtesy of GroundWork Renewables, Inc.
Long Term Resource Reference Frame
Satellite data provides the consistent, long term reference frame needed to derive reliable
estimates of P50, P90, variability, etc.
Satellite Data Modeling
Clear sky and cloudy sky errors need to be independently targeted in any solar satellite data tuning process!
Clear Sky Irradiance Radiative Transfer Model
+Cloudy Sky Irradiance
Cloud Modulation
Satellite Ground Tuning Methodology
Measure-correlate-predict (MCP) and Model Output Statistics (MOS) corrections often ignore individual satellite irradiance errors
Clear sky tuning
Cloudy sky tuning
Satellite DNI/DHI Rebalancing
Time of Day4 8 12 16 20
DNI
DHI
GHI OriginalRebalanced
GHI = COS(Z)*DNI + DHI
Not rebalancing data can improperly skew POAI calculations in energy simulations (PVsyst, SAM, etc.)
4 8 12 16 20Time of Day
GHI
Study Methodology Data inputs:
• Hourly averaged irradiance ground data (14 SURFRAD and ISIS sites)• Hourly averaged SolarAnywhere irradiance data
The satellite-to-ground tuning process is applied to fixed segments (1-24 months) of ground data which are rolling by a one month interval over 5 years
The tuning results are applied to 5 years of satellite data and residual error metrics are calculated
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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
3 month example
Individual Site Results: Albuquerque, NM
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Seasonal influences can be dramatic with less than a year of data Error results stabilize significantly with year + timeframes
Individual Site Results: Goodwin Creek, MS
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Seasonal influences can be dramatic with less than a year of data Error results stabilize significantly with year + timeframes
Individual Site Results: Penn State, PA
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Seasonal influences can be dramatic with less than a year of data Error results stabilize significantly with year + timeframes
Overall Results
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Decreasing envelope of uncertainty with increased month selection independent of location
Key Takeaways
Seasonal impacts can be amplified with less than a year of ground data
We can provide uncertainty for tuning studies based on X amount of ground data
See further results presented at IEEE PVSC
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The information herein is for informational purposes only and represents the current view of Clean Power Research, L.L.C. as of the date of this presentation. Because Clean Power Research must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Clean Power Research, and Clean Power Research cannot guarantee the accuracy of any information provided after the date of this presentation. CLEAN POWER RESEARCH, L.L.C. MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
Thank you
Skip DiseSolarAnywhere Prod. Manager
johndise@cleanpower.com
Adam KankiewiczSolar Research Scientist adamk@cleanpower.com
Please feel free to contact us for any details or clarification related to presentation
Tom StaplesSenior Account Executive tstaples@cleanpower.com
Impact of Non-Average Years on Tuning
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Ground site Year Residual MBE Variance from long term annual average
Penn State
2010 0.67% 1.48%2011 0.55% -4.16%2012 -1.52% 1.46%2013 0.39% -2.29%
Goodwin Creek
2010 0.01% 4.40%2011 0.21% 1.15%2012 0.17% 1.90%2013 1.25% -4.33%
Albuquerque
2010 -0.59% 0.15%2011 0.97% -0.84%2012 1.11% -3.91%2013 0.93% -1.39%
CPR tuning is not affected by above or below average solar irradiance years
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