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Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
10 June 2014
High-Frequency Irradiance and Power Output for Grid Integration and Storage Evaluations Jaclyn Frank
Senior Research Scientist
Dr. Michael Brower
Chief Technical Officer
Senior Research Scientist
Dr. Philippe Beaucage
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Outline
• Background on solar integration study
• Technical approach:
– coupled mesoscale-microscale model + onsite measurements
• Validation
• Results
– Diurnal profiles
– Ramp frequency distribution
• Summary
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Hawaii Solar Integration Study
• 2 years of 2-second PV output
• Utility-scale & distributed rooftop PV
• Single-axis tracking, fixed rooftop
• 500+ MW hypothetical sites
• Collaboration with HECO, GE, NREL
• Determine impact of increasing renewables on the electrical grid
• Oahu and Maui
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Available Measured Data
• HECO’s “Sun Power for Schools”
– 6 Oahu Schools 2007-2008
– 15-minute average GHI and PV
• NREL Measurement and Instrumentation Data Center
– 4 Oahu stations with 1-second data since June 2009
– 2 stations with all components
• Oahu Pyranometer Array
– 17 instruments within 1 km2
– 1-second GHI since March 2010
• ASOS – 5-minute cloud cover
4 9
12
17
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Challenges of Modeling High-Frequency PV
• Numerical models and satellite imagery won’t get high-frequency ramps correctly
• Point measurements do not represent plant-wide aggregate
Stochastic-kinematic cloud model developed to address these issues
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Overview of Modeling Approach
Numerical Weather Prediction Model
• Solar irradiance
• Cloud cover fraction
• Cloud-base wind speed, direction
• 10-m wind speed, 2-m temperature (for power conversion)
Stochastic-Kinematic Cloud Model
• Cloud location
• Cloud size
• Cloud opacity
• Cloud overlap and edge effects
• Solar irradiance and power generation
MESOSCALE MICROSCALE
Reference: Beaucage, P., M.C. Brower, J.D. Frank and J.D. Freedman (2012). "Development of a Stochastic-Kinematic Cloud Model To Generate High-Frequency Solar Irradiance and Power Data”. Proceedings of the ASES conference, Boulder (CO), May 14th, 2012
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Cloud Animation
Oahu • June 4th, 2007 • 6 AM – 7 PM
• Area ~100x100 km2 • Background = cloud cover
fraction from mesoscale model
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Conversion to Power
• Extract irradiance at each point
• Convert to power with in-house software
• Aggregate over utility-scale plant or distributed PV area
1 km
1 km
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Reality Check: Does Modeled Data Match Observations?
• An exact match with observations is impossible
• Synthesized data should be statistically indistinguishable from real data for parameters of interest
• What are the parameters of interest? – Mean output
– Diurnal, monthly patterns
– Dynamic behavior (spectrum of ramps) as a function of plant size/aggregation
– Correlation between sites
A typical pattern of direct and diffuse horizontal irradiance on Oahu
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Validation - Irradiance Diurnal Mean Profiles
• January 2011
• Diurnal means, max match well for each component
• High bias in warm months, low bias in cool months
GHI DNI DHI
Model Mean Obs Mean Model Max Obs Max Clear Sky
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
HECO Station Validation: 2010-2011
• GHI bias (%)
• Small, acceptable low bias: 2%
• Model performs better on western side of Oahu
• Perhaps not fully capturing the impact of mountains?
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Irradiance Ramps – Aggregation of Several Measurements
5 HECO stations
NREL17
6-sec 1-min 10-min
Modeled ramps slightly more variable than observed, but match distributions well
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Applications for Grid Integration and Storage Evaluation
• Estimating sustainable penetration levels of solar energy in an electrical grid – Optimizing spatial distribution and
size of solar PV arrays
• Sizing of battery bank for storage to reduce:
– down ramps
– solar curtailment
http://www.solsystemscompany.com/blog/wp-content/uploads/2014/05/Solar+Battery.jpg
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Summary
• Generated 2 years of 2-second PV output at 80+ hypothetical sites for the Hawaii Solar Integration Study
• Mean diurnal profiles fit well with available high-quality observations
• Ramp distributions agree well with observed
• Future work: – Test model in other climates
– Validate further with utility-scale PV data
Useful tool to estimate ramps at hypothetical (pre- construction) PV sites
New Approach: Mesoscale NWP model + microscale stochastic-kinematic cloud model
Albany, New York | Barcelona, Spain | Bangalore, India | awstruepower.com | +1 877-899-3463
©2013 AWS Truepower, LLC
Thank You
+1 877-899-3463
awstruepower.com
Dr. Philippe Beaucage
Jaclyn Frank