Download pdf - Solar Resource Assessment: Why it Matters

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


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


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


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


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


Campaign Data Summaries

• Site Description

• Solar Statistics

• Meteorological Statistics

• Monthly and Diurnal T dTrends

O&M S• O&M Summary


INVESTMENT GRADE ANALYSIS


Developing a Long‐Term Projection

Modeled

On‐Site Data

Observed

Data

Reference Data

Long‐Term Meteorological Characteristics

Objective Review of Resource and Energy Potential


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


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


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/


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


Adjusting to the Long‐Term

Short Period of Long Period of 12001200

On‐site Data Reference Data

Measure Correlate Predict600

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Measure ‐ Correlate ‐ Predict

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ReferenceStation Site250

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L t R E ti ti50

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thly Irradiation (kW

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Long‐term Resource Estimation at the Project Site

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Long‐Term Reference Data On‐Site Measured

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Long‐Term Reference Data On‐Site Measured


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


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.


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


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


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
