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Characterizing solar resources and local meteorological attributes is an important first-step in the review of any solar energy project. While residential and light commercial projects may require only a cursory assessment, larger distributed generation and utility-scale projects necessitate a more rigorous evaluation. AWS Truepower’s President and CEO, Bruce Bailey and Director of Solar Services, Marie Schnitzer will cover the importance of using established resource assessment methods to lower project risk and improve project and site characterization. During the webinar they will share lessons-learned from the wind industry and provide insight on best practices in desktop studies, on-site monitoring programs, and field activities.
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ALBANY • BARCELONA • BANGALORE September 2010
SOLAR RESOURCE ASSESSMENT: WHY IT MATTERSSOLAR RESOURCE ASSESSMENT: WHY IT MATTERS
BRUCE BAILEY, PRESIDENT & CEO
MARIE SCHNITZER, DIRECTOR OF SOLAR SERVICES
463 NEW KARNER ROAD | ALBANY, NY 12205awstruepower.com | [email protected]
Topics Addressed
• The Importance of Solar Resource Assessment
• Best Practices for On‐Site Monitoring
• Investment Grade Analysis
• Key Messages
• Questions
©2010 AWS Truepower, LLC 2
Importance of Solar Resource Information
Project Lifecycle Considerations:• Early Development Phase• Early Development Phase
– Prospecting and Site Screening– Site Comparison and SelectionSite Comparison and Selection
• Pre‐Construction and Financial Readiness Phase– Long‐Term Energy Assessment– Economic ViabilityO ti l Ph• Operational Phase– Performance Verification– Utility ForecastingUtility Forecasting
Characterize the Spatial and Temporal Variability of System Output
©2010 AWS Truepower, LLC 3
The Path to an Investment Grade Analysis
• Conduct an On‐Site Measurement Campaign
• Procure High‐Quality Reference Data
• Analyze Data Sets and Predict Long‐Term Resource
• Quantify Data Uncertainties
• Conduct Energy Production Analysis
Source: photos.com
©2010 AWS Truepower, LLC 4
ON‐SITE MONITORING PROGRAMS©2010 AWS Truepower, LLC
Solar Radiation Components
• Direct Normal Irradiance (DNI)
• Diffuse Horizontal Irradiance (DHI)
• Global Horizontal Irradiance (GHI)Source: nrel.gov
Source: esri.com
©2010 AWS Truepower, LLC 6
Source: kippzonen.com
Attributes of On‐Site Monitoring
• On‐site monitoring provides significant value to g p gassessing a project’s potential, translating to higher confidence in energy estimates.
– Accurate Representation of the Project Site– Customizable for Various Technologies (e.g.,
S ) d iPV or CSP) and Various Users – Flexible Equipment Options and Costs
Small Environmental Footprint– Small Environmental Footprint– Straight‐Forward Installation & Operation– Self‐Contained Communications and PowerSelf Contained Communications and Power
Supply
©2010 AWS Truepower, LLC
On‐Site Monitoring Programs – Best Practices
• Measurement Plan– Solar Instrumentation– Meteorological: Temperature,
Wind Speed, Precipitation– Balance of System– Sampling/Recording Rate– Measurement Period
• Installation and Commissioning– Site Selection– Audit and Sensor
Verification– Equipment Orientation– Communications and Data QA– System Security– Documentation
©2010 AWS Truepower, LLC 8
On‐Site Monitoring Programs – Best Practices
• Maintenance
– Regular Schedule
– Clean and Level Instrumentation
– Verify Site Security and Overall Conditions
• Data Validation and Quality Control
Regular System and Data Inspection– Regular System and Data Inspection
– Comparison with Reference Data
Extreme or Suspect Values– Extreme or Suspect Values
Getting the Highest Quality Data
©2010 AWS Truepower, LLC 9
Campaign Data Summaries
• Site Description
• Solar Statistics
• Meteorological Statistics
• Monthly and Diurnal T dTrends
O&M S• O&M Summary
©2010 AWS Truepower, LLC 10
INVESTMENT GRADE ANALYSIS
©2010 AWS Truepower, LLC
Developing a Long‐Term Projection
Modeled
On‐Site Data
Observed
Data
Reference Data
Long‐Term Meteorological Characteristics
Objective Review of Resource and Energy Potential
©2010 AWS Truepower, LLC 12
Other Sources for Solar Resource Data
• Modeled Data
– National Solar Radiation Database (NSRDB)
– International Databases
– Solar Maps
• Observed Reference Data
N i l N k– National Networks
– Regional and State Networks
I t ti l S
http://eosweb.larc.nasa.gov/cgi‐bin/sse/sse.cgi?+s01#s01
– International Sources
©2010 AWS Truepower, LLC 13
Modeled Solar Resource Data
• Characterizations– Availability
– Long Periods of Record
– Consistent Methodology
• Limitations• Limitations– Spatial Resolution
– Potentially Large BiasesPotentially Large Biases
– High Data Uncertainty Source: http://www.nrel.gov/gis/solar.html
“Originally intended for use to compare various modeling scenarios –NOT for absolute performance based on climate.”
NREL, Solar Radiation Data Sets, 2008 Solar Resource Assessment Workshop
©2010 AWS Truepower, LLC 14
Observed Reference Data
• The potentially higher accuracy of ground data may result in more i f j ’ i l b h faccurate estimates of a project’s potential, but there are very few
high quality solar measurement stations.
• Characterizations
– Complements Modeled Data Set
P i i P j Si– Proximity to Project Site
– Potentially Reduced Data Uncertainty
• Limitations• Limitations
– Instrumentation Differences
– Varying Maintenance Practices SURFRAD Reference Station Desert RockVarying Maintenance Practices
Using multiple sources of data can result in a more robust resource analysis.
SURFRAD Reference Station – Desert Rock. http://www.srrb.noaa.gov/surfrad/
©2010 AWS Truepower, LLC
Using multiple sources of data can result in a more robust resource analysis.15
Considerations for Regionally Observed Data Sets
• Site Location and Exposure• Proximity to Project Site
ReferenceStation
• Period of Record• Data Trends
D t R R t
Site
• Data Recovery Rate• Site Maintenance • Instrument CalibrationInstrument Calibration• Correlation Between Sites
Source: photos.com
©2010 AWS Truepower, LLC 16
Adjusting to the Long‐Term
Short Period of Long Period of 12001200
On‐site Data Reference Data
Measure Correlate Predict600
800
1000
Site GHI (W/m
2 )
600
800
1000
Site GHI (W/m
2 )
Measure ‐ Correlate ‐ Predict
0
200
400
0 200 400 600 800 1000 1200
Target
0
200
400
0 200 400 600 800 1000 1200
Target
ReferenceStation Site250
300
Wh/m
2 )
250
300
Wh/m
2 )
Reference Site GHI (W/m2)Reference Site GHI (W/m2)
Site
L t R E ti ti50
100
150
200
Mon
thly Irradiation (kW
50
100
150
200
Mon
thly Irradiation (kW
Long‐term Resource Estimation at the Project Site
0
Jan‐02
Jul‐0
2
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Jul‐0
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Jul‐0
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M
Long‐Term Reference Data On‐Site Measured
0
Jan‐02
Jul‐0
2
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3
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M
Long‐Term Reference Data On‐Site Measured
©2010 AWS Truepower, LLC
Energy Production Analysis
Sun Position, Surroundings, H i tHorizon, etc
Project Location
Component Global/Diffuse o po eSelection, Orientation, Tracking, Row Spacing, etc
Global/Diffuse Horizontal,
Temperature, Wind Speed
Energy Analysis
Plant DesignResource
System Losses
Soiling, Shading, Incident Angle,
Mismatch Wiring
Losses
©2010 AWS Truepower, LLC
Mismatch, Wiring, Availability, etc
Relative Uncertainties of On‐Site Monitoring
Source: austincollege.eduSource: lockheedmartin.com
Data Source Typical Annual Uncertainty
Satellite Modeled (NSRDB) ± 8‐15%
Pyranometer (GHI) ± 3‐5 %
Pyrheliometer (DNI) ± 2‐3%
Reducing the uncertainties in the solar resource make the project more attractive to investors.
©2010 AWS Truepower, LLC 19
Uncertainty in the Long‐Term Projections
Uncertainty Considerations
• Measurement• Measurement
• Inter‐Annual Variability
• Representativeness of Monitoring PeriodRepresentativeness of Monitoring Period
• Spatial Variability
• Transposition to Plane of Array
• Simulation and Plant Losses
Confidence in Energy EstimatesConfidence in Energy Estimates
• Probability Analysis
• P50, P75, P90, P95, P99
The uncertainty of data used in an assessment needs to becharacterized and applied to the long‐term projections
©2010 AWS Truepower, LLC
Key Messages
• Solar resource assessment is a sound investment• Solar resource assessment is a sound investment
• Utilize all available data sets in an resource analysis
• Consider the factors that impact the quality of the data sets
• Thorough resource assessments lead to more accurate energy estimates
• Detailed analysis of the resource and better characterization of the project site leads to an investment grade projectp j g p j
©2010 AWS Truepower, LLC 21
Image source: photos.com
Resource Assessment
Energy AssessmentForecasting
Supporting the Complete
Lifecycle
Project Consulting
Independent
Performance Assessment
QUESTIONS?Independent Engineering
& Due Diligence
Toll Free: 1‐877‐899‐3463Ph: 518‐213‐0044Email: [email protected] Web: awstruepower.comWeb: awstruepower.com
©2010 AWS Truepower, LLC
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