Acceptance Test of Solar Collector Fields -...

Acceptance Test of Solar Collector Fields

Models, Measurement, Evaluation, Uncertainty

www.DLR.de • Chart 1 > 4th SFERA Summerschool > E. Lüpfert, N.Janotte > 16th May 2013

4th SFERA Summer School, 16th May 2013, Hornberg

Eckhard Lüpfert, Nicole Janotte

Overview

• Introduction and Motivation• Performance Testing• Application to Solar Fields

• Test Equipment• Testing/Acceptance Procedures

• Conclusion• Outlook


Power Blocksteam cycle

turbine, condenser49.9 MW

Heat Transfer & Buffer1.01 GWh

8 hours capacity

Solar Fieldparabolic trough

collector field152 loops, 497 040

m2

Andasol Parabolic Trough Plant Scheme

www.solarpaces.org

> 4th SFERA Summerschool > E. Lüpfert, N.Janotte > 16th May 2013 www.DLR.de • Chart 3

Introduction and MotivationAcceptance Testing of Solar Collector Fields

„Is the solar field performing according to expectations and will it continue to do so in the years to come?“

PERFORMANCE TESTVerification of the performance of the solar field to meet specifications

Important milestone of implementation of CSP power plant projects:• Transfer of ownership• Maturity of payments (bonus/penalty)• Start of warranty period


Motivation for Dealing with Acceptance Testing in Solar Research • Important technical, legal and financial implications of solar field

performance/ acceptance tests:→ annual yield (payback of initial investment)→ impact on implementation of CSP technologies

• Scientific basis required for sound acceptance criteria and procedures• Relevance of measurement uncertainty for interpretation of test results• Simplification and speed up by standardisation

Large scale implementation of Parabolic Trough Solar Power Plants


Solar Field Performance (annual)Energy Conversion of a Parabolic Trough System


Principle of Performance Testing

• Determination of useful solar power of the solar field• Key measurands

• in- and outlet temperatures, mass flow rate• Solar field operation (focus, cleanliness)• Ambient conditions (temperature, irradiance,…)

• Relevant testing conditions


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in

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T

)(pHTFfield

ToutTinmHTF

Loop Piping and Instrumentation


Performance Modelling Approaches


• analyticalvarious models available based on component characteristics and heat balances

limited benefits in collector/field qualification

• engineering/groupedidentification of most influential factors (structural/optical, temperature dependence, others)

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optical performance thermal losses

Application to Solar Fields

Challenges• Extent of solar field and transit times• Representativeness of test results for long-term annual performance• Significance of test results• Acceptance criteria


[D. Kearney, 2011]

Current Practice for Solar Field Performance Testing• Individual agreement between parties• Acceptance based on agreement of test results and model performance

predictions• For example:

• Provisional acceptance (several days upon commissioning)• Final acceptance after one year of solar field performance

→ costly, problematic in terms of significance


Test EquipmentStandard Built-In Power Plant Instrumentation• Solar tracker with irradiation sensors• Ambient and wind sensors• Vortex or wetted ultrasonic flow meter• Immersion temperature sensors• Plant tracking monitoring• Cleanliness measurements• Plant data processing


Test EquipmentMobile Field Laboratory• Mobile solar tracker with irradiation sensors• Ambient temperature and wind sensors• Clamp-on ultrasonic flow meter• Clamp-on temperature sensors• Clamp-on tracking monitoring• Cleanliness measurement• Mobile data loggers


Comparison of Measurement Equipment Options


precision & accuracy

independence

traceability & recalibration

plant operation interruption

mounting/dismounting effort

flexibility

leakage hazard

lower effort → short- to medium-time measurements

high effort → long-time measurements

clamp-on built-in

sensor specific

possible no

easy difficult

no yes

low high

good poor

no yes

Performance Test Uncertainty


• Scenarios• High Precision (reference case)• Built-In Sensor Equipment (state of the art)• Mobile Field Laboratory (innovative)

• GUM evaluation

uc(ηth) at 1σ0.59%1.30%1.10%

Different Approaches Towards Performance Testing

1. Measurement of solar field performance

2. Generation of performance predictions of (black box) solar field model under test conditions

3. Evaluation of agreement of measured and predicted performance

1. Measurement of solar field performance

2. Identification of key performance parameters and their uncertainty from test data

3. (probabilistic) prediction of annual yield

Verification of predictions of given solar field performance model

Identification of performance parameters and annual prediction


Selection of suitable test daysrepresentative for annual operation enabling identification of representative

parameters

Verification of Model PerformanceMethod• Several short duration thermal power tests:

The thermal output and efficiency measured under clear sky conditions for a short period of steady-state operation (exemplary allowable variability in the range of 0.2% to 0.5% for temperatures, flow rate and beam irradiance)

• A multi day continuous energy test: The integrated power output is determined for a number of consecutive days under clear sky or partly cloudy conditions

• Generation of (black box) model performance for test conditions

• Comparison of test and model performance


Testing and Acceptance CriteriaVerification of Model Performance

• Test day selection to match/represent typical annual solar field generation characteristics

• Acceptance criteria formulation in terms of agreement between test results and model predictions

→ assuring annual solar field yield


Advanced Testing and ModellingTesting and Acceptance CriteriaParameter Identification


PerformanceTesting

Parameter Identification

YieldPrediction

www.DLR.de • Chart 19

measurement scenario testing conditions

parameter set + uncertaintiesη 0.75 0.012

…

p=95%

Review of testing requirements

parameterizedsolar field model

?

parametermodification

initialparameters

predicted yieldE ± 4%

Performance Parameter IdentificationTesting and Acceptance Criteria • Consideration of mixing effects and residence times in header and loop

piping in addition to performance equation for full solar field model

• Mere field operation at nominal inlet and outlet temperatures insufficient to identify representative parameters

• Decoupling of optical and thermal effects requires operation at different temperature levels (in addition to dynamic heat-up and cool-down phases)

• Requirements on variation of angle of incidence during testing (seasons) depend on IAM model formulation

• Acceptance on the basis of uncertainty to which annual yield can be predicted


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Existing Performance Standards and Ongoing Standardization• ASHRAE 93-86: Methods of Testing to Determine the

Thermal Performance of Solar Collectors• EN 12975: Thermal solar systems and components - Solar

collectors - Part 2: Test methods • ASTM 905: Standard Test Method for Determining Thermal

Performance of Tracking Concentrating Solar Collectors• PTC 19 Uncertainty• ASME PTC 52: Performance Test Code for Concentrating

Solar Power Plants


collectorscale

Conclusions and Outlook

• Solar field performance testing is a key element when commissioning any solar field

• Performance is a delicate issue for all parties involved, thus working with /obtaining actual field data is challenging

• Two solar field acceptance methods proposed in addition to current practice:

• Confirmation of actual performance to meet model predictions• Parameter identification and prediction of annual yields

• Significance of test results is improved

• Better/optimum significance of performance test results possible using independent calibrated sensors at well defined standard measurement points

• Parameter identification and yield prediction approach are currently being demonstrated on actual field data


Literature• D. Kearney. Utility-Scale Parabolic Trough Solar Systems: Performance

Acceptance Test Guidelines (April 2009 - December 2010). Tech. Rep. NREL/SR-5500-48895, National Renewable Laboratory, Golden Colorado (USA), 2011.

• N. Janotte. Requirements for Representative Acceptance Tests for the Prediction of the Annual Yield of Parabolic Trough Solar Fields, dissertation RWTH Aachen University, 2012

• Standards• Guide to the Expression of Uncertainty in Measurement. International

Organisation for Standardisation, Geneva (Switzerland), second Ed., 1995.• ASHRAE 93-96: Method of Testing to Determine the Thermal Performance of

Solar Collectors. New York (USA), 1978.• ASTM-905: Standard Test Method for Determining Thermal Performance of

Tracking Concentrating Solar Collectors. West Conshohocken (USA), 2001.


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