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Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
Solar Resource Assessment: Why it Matters
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Solar Resource Assessment: Why it Matters

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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 …

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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  • 1. ALBANY •   BARCELONA  •  BANGALORE September 2010 SOLAR RESOURCE ASSESSMENT: WHY IT MATTERS SOLAR RESOURCE ASSESSMENT: WHY IT MATTERS BRUCE BAILEY, PRESIDENT & CEO MARIE SCHNITZER, DIRECTOR OF SOLAR SERVICES 463 NEW KARNER ROAD | ALBANY, NY 12205 awstruepower.com | info@awstruepower.com
  • 2. 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
  • 3. Importance of Solar Resource Information Project Lifecycle Considerations: • Early Development Phase Early Development Phase  – Prospecting and Site Screening – Site Comparison and Selection Site Comparison and Selection • Pre‐Construction and Financial  Readiness Phase – Long‐Term Energy Assessment – Economic Viability • OOperational Phase ti l Ph – Performance Verification – Utility Forecasting Utility Forecasting Characterize the Spatial and Temporal Variability of System Output ©2010 AWS Truepower, LLC 3
  • 4. 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
  • 5. ON‐SITE MONITORING PROGRAMS ©2010 AWS Truepower, LLC
  • 6. Solar Radiation Components • Direct Normal Irradiance (DNI) • Diffuse Horizontal Irradiance (DHI) Source: nrel.gov • Global Horizontal Irradiance (GHI) Source:  esri.com Source: kippzonen.com ©2010 AWS Truepower, LLC 6
  • 7. Attributes of On‐Site Monitoring • On‐site monitoring provides significant value to  gp g assessing a project’s potential, translating to  higher confidence in energy estimates. – Accurate Representation of the Project Site – Customizable for Various Technologies (e.g.,  PV or CSP) and Various Users  S ) d i – Flexible Equipment Options and Costs – Small Environmental Footprint Small Environmental Footprint – Straight‐Forward Installation & Operation – Self‐Contained Communications and Power Self Contained Communications and Power  Supply ©2010 AWS Truepower, LLC
  • 8. 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
  • 9. 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
  • 10. Campaign Data Summaries • Site Description • Solar Statistics • Meteorological Statistics • Monthly and Diurnal  Trends T d • O&M S O&M Summary ©2010 AWS Truepower, LLC 10
  • 11. INVESTMENT GRADE ANALYSIS ©2010 AWS Truepower, LLC
  • 12. Developing a Long‐Term Projection On‐Site  Modeled  Data Data Observed  Reference  Data Long‐Term Meteorological Characteristics Objective Review of Resource and Energy Potential ©2010 AWS Truepower, LLC 12
  • 13. Other Sources for Solar Resource Data • Modeled Data – National Solar Radiation  Database (NSRDB) – International Databases – Solar Maps • Observed Reference Data – N i National Networks lN k http://eosweb.larc.nasa.gov/cgi‐bin/sse/sse.cgi?+s01#s01 – Regional and State Networks – I t International Sources ti lS ©2010 AWS Truepower, LLC 13
  • 14. Modeled Solar Resource Data • Characterizations – Availability – Long Periods of Record – Consistent Methodology • Limitations – Spatial Resolution – Potentially Large Biases Potentially 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
  • 15. Observed Reference Data • The potentially higher accuracy of ground data may result in more  accurate estimates of a project’s potential, but there are very few  i f j ’ i l b h f high quality solar measurement stations. • Characterizations – Complements Modeled Data Set – P i i Proximity to Project Site P j Si – Potentially Reduced Data Uncertainty • Limitations – Instrumentation Differences – Varying Maintenance Practices Varying Maintenance Practices SURFRAD Reference Station Desert Rock SURFRAD Reference Station – Desert Rock.  http://www.srrb.noaa.gov/surfrad/ Using multiple sources of data can result in a more robust resource analysis. Using multiple sources of data can result in a more robust resource analysis. ©2010 AWS Truepower, LLC 15
  • 16. Considerations for Regionally Observed Data Sets • Site Location and Exposure Reference • Proximity to Project Site Station • Period of Record Site • Data Trends • Data Recovery Rate D t R R t • Site Maintenance  • Instrument Calibration Instrument Calibration • Correlation Between Sites Source: photos.com ©2010 AWS Truepower, LLC 16
  • 17. Adjusting to the Long‐Term Short Period of  Long Period of  1200 On‐site Data Reference Data 1000 Target Site GHI (W/m 2 ) 800 600 Measure ‐ Correlate ‐ Measure Correlate Predict 400 200 0 0 200 400 600 800 1000 1200 Reference Site GHI (W/m 2 ) 300 Reference Wh/m 2 ) Station 250 Site Monthly Irradiation (kW 200 150 100 50 Long‐term Resource Estimation  L t R E ti ti M 0 Jan‐02 Jan‐03 Jan‐04 Jan‐05 Jan‐06 Jan‐07 Jan‐08 Jan‐09 Jul‐02 Jul‐03 Jul‐04 Jul‐05 Jul‐06 Jul‐07 Jul‐08 Jul‐09 at the Project Site Long‐Term Reference Data On‐Site Measured ©2010 AWS Truepower, LLC
  • 18. Energy Production Analysis Sun Position,  Surroundings,  Horizon, etc H i t Project  Location Global/Diffuse  Global/Diffuse Component  o po e Horizontal,  Resource Energy  Plant  Selection,  Design Orientation,  Temperature,  Wind Speed Analysis Tracking, Row  Spacing, etc System  Losses Soiling, Shading,  Incident Angle,  Mismatch, Wiring,  Mismatch Wiring Availability, etc ©2010 AWS Truepower, LLC
  • 19. Relative Uncertainties of On‐Site Monitoring Source: lockheedmartin.com Source: austincollege.edu 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
  • 20. Uncertainty in the Long‐Term Projections Uncertainty Considerations • Measurement • Inter‐Annual Variability • Representativeness of Monitoring Period Representativeness of Monitoring Period • Spatial Variability • Transposition to Plane of Array • Simulation and Plant Losses Confidence in Energy Estimates Confidence in Energy Estimates • Probability Analysis • P50, P75, P90, P95, P99 The uncertainty of data used in an assessment needs to be characterized and applied to the long‐term projections ©2010 AWS Truepower, LLC
  • 21. 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 project p j g p j Image source: photos.com ©2010 AWS Truepower, LLC 21
  • 22. Resource  Assessment Energy  Forecasting Assessment Supporting  the Complete  Lifecycle Performance  Project  Assessment Consulting Independent  Independent QUESTIONS? Engineering  &  Due Diligence Toll Free: 1‐877‐899‐3463 Ph: 518‐213‐0044 Email: info@awstruepower.com  Web: awstruepower.com Web: awstruepower.com ©2010 AWS Truepower, LLC

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