Calibration methods for rotating shadowband irradiometers and optimizing the  calibration duration

Jessen, Wilko; Wilbert, Stefan; Nouri, Bijan; Geuder, Norbert; Fritz, Holger

doi:10.5194/amt-9-1601-2016

Cited by 9 publications

(5 citation statements)

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“…Note that we only refer to the constants a to f for the sunshape measurement here and not to the calibration constants required for DNI, GHI and the diffuse irradiance. The calibration constants for these standard irradiance measurements must of course be instrument specific and also a recalibration is required every two years [5,6]. It was found that no individual sunshape calibration is required for each instrument, but that the algorithm can be used with the same constants for all studied RSIs.…”

Section: Validation Results and Calibration Requirementsmentioning

confidence: 99%

Sunshape measurements with conventional rotating shadowband irradiometers

Wilbert

Röger

Csambor

et al. 2018

AIP Conference Proceedings

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Because of forward scattered radiation in the atmosphere, the circumsolar region closely surrounding the solar disk looks very bright. The radiation coming from this region, the circumsolar radiation, is in large part included in direct normal irradiance (DNI) measurements at the usual 2.5° pyrheliometer opening half angle, but only partially intercepted by the receivers of focusing solar collectors. Therefore, circumsolar radiation measurements are recommended to be included in solar resource assessment. Circumsolar radiation can be characterized using the radial angular distribution of the radiance around the center of the sun-the so-called sunshape. Several sunshape measurement methods have been developed recently. Most approaches use cameras or pyrheliometers with different apertures which require daily maintenance. The Rotating Shadowband Irradiometer (RSI) based method discussed here uses a conventional RSI without any hardware modification to enable sunshape measurements without affecting the RSI's fundamental function as a DNI measurement device. Thus, it allows to measure circumsolar radiation without any additional hardware and with significantly lower maintenance requirements. The presented RSI-based sunshape measurement algorithm has been validated with four RSIs and more than two years of data. After a short description of the method to derive the circumsolar contribution, the validation results are shown. Then the required calibration method is discussed, followed by the results from the measurement campaigns at four sites in Spain, India and Morocco. It was found that no individual calibration is required per instrument and the algorithm can be used for automatic data processing so that common RSI stations can measure the sunshape with comparably low extra effort. Furthermore, we explain how to derive sunshapes from the RSI measurements.

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Section: Validation Results and Calibration Requirementsmentioning

confidence: 99%

Sunshape measurements with conventional rotating shadowband irradiometers

Wilbert

Röger

Csambor

et al. 2018

AIP Conference Proceedings

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“…Examples of drift in the GHI calibration constants obtained from Geuder et al (2008) were later investigated for nine sensors in Geuder et al (2010) and Jessen et al (2016). For recalibration periods between 2 years and 3.75 years, changes in this GHI calibration constant were below 1% in most cases.…”

Section: Calibration Methods For Rsismentioning

confidence: 99%

“…These longer calibration periods provide a database for the analysis of systematic signal deviations and measurement accuracy. An analysis of the dependence of the calibration constants on the duration of the calibration period, as well as more details on two possible calibration methods, are presented in Jessen et al (2016) and Geuder et al (2012). Data quality is analyzed and compared to the reference irradiances.…”

Section: Calibration Methods For Rsismentioning

confidence: 99%

“…Recalibration is recommended at least every 2 years. An overview of current RSI calibration methods is presented in Jessen et al (2016), and more details can be found in Geuder et al (2008Geuder et al ( , 2010 and Kern (2010). A case study for the accuracy achievable by different combinations of correction functions and calibration methods is summarized in Chapter 6.…”

Section: Calibration Methods For Rsismentioning

confidence: 99%

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Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

2017

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Designing, financing, and operating successful solar heating, concentrating solar power, and photovoltaic systems requires reliable information about the solar resource available and its variability over time. In the past, seasonal and daily variability has been studied and understood; however, with new solar technologies becoming more important in energy supply grids, small time-scale effects are critical to successful deployment of these important low carbon technologies. A vital part of the bankability of solar projects is to understand the variability of the solar resource so that supply and storage technologies can be optimized.This handbook is the result of 10 years of international collaboration carried out by experts from the International Energy Agency's (IEA's) Solar Heating and Cooling (SHC), Solar PACES, and Photovoltaic Power Systems Technology Collaboration Programmes. Under IEA SHC Task 46: Solar Resource Assessment and Forecasting, experts from 11 countries produced information products and best practices on solar energy resources that will greatly benefit project developers and system operators as well as assist policymakers in advancing renewable energy programs worldwide.Meteorologists, mathematicians, solar technology specialists, and other key solar resource experts from around the world joined forces to further our understanding of the sun's temporal and spatial variability through benchmarking satellite-derived solar resource data and solar forecasts, developing best practices for measuring the solar resource, and conducting research to improve satellite-based algorithms. The results of IEA SHC Task 46 are useful to a wide range of users of solar heating and cooling, photovoltaics, and concentrating solar power systems and of building developers and owners as well as anyone else who needs to understand and predict sunlight for agricultural or other purposes.The earlier edition of the handbook, which was published in 2015, is used worldwide as a reference for each stage of a solar energy project. Since that time, there has been substantial growth in the interest in high-quality "bankable" solar resource data. This revision adds significant new methods so it will be even more useful.This publication is a summary that details the fundamentals of solar resources as well as captures the state of the art. For those wanting more depth, it also provides the references where more detailed information can be found.I would like to acknowledge the leadership of the National Renewable Energy Laboratory and express appreciation to the U.S. Department of Energy for producing the handbook and incorporating results from IEA SHC Task 46. Ken Guthrie Chair, IEA Solar Heating and Cooling Technology Collaboration Programme June 2017This report is available at no cost from the National Renewable Energy Laboratory at www.nrel.gov/publications. Preface Dave Renné Dave Renné Renewables, LLCAs the world looks for carbon-free sources to meet final energy demand associated with heat, electrical power, and transport, ...

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“…Additional outdoors calibration methods that compare the photodiode pyranometers to thermopile pyranometers are described by Jessen, Kern, and Vignola and, depending on the calibration method, different calibration factors can be obtained. [ 11,16,17 ] For the method used in this study, the calibration yields individual calibration factors for GHI and DHI. [ 10 ]…”

Section: Correction Factorsmentioning

confidence: 99%

Uncertainty Calculation Method for Photodiode Pyranometers

Forstinger

Wilbert²,

Driesse³

et al. 2021

Solar RRL

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For project development and monitoring of large-scale solar power plants, solar irradiance ground measurements are of crucial importance. Photodiode pyranometers are widely used for such applications, especially at remote locations. The advantages compared to most thermopile pyranometers are a fast response time in the order of microseconds, lower costs, no thermal offsets, and a higher robustness against sensor soiling. In contrast to most thermopile sensors, which use clear domes as entrance windows, most photodiode pyranometers use diffusor disks as entrance windows. The scattering contribution of the soiling losses is smaller in the case of a diffusor and therefore the soiling effect is reduced for most photodiode pyranometers. [1,2] Note that ventilators might also reduce the soiling losses. However, photodiode pyranometers have higher measurement errors compared to thermopile pyranometers which are partly systematic and can cause a noticeable bias in solar resource measurements. [3] In comparison with the typical domes of thermopile pyranometers, the diffusor disk of photodiode pyranometers causes a comparably high incidence angle dependence, although its shape is already designed to limit the effect. [4] A fully flat diffusor disk, only exposed to the radiation via its up-facing surface, would cause lower sensitivities for high incidence angles. This is related to the increase of the surface reflectance with larger incidence angles and the extension of the light path through the diffusor. Most diffusor disks are therefore curved or use not only the upper circular surface of a cylinder-shaped receiver, but also the lateral area. Furthermore, photodiode pyranometers show a higher temperature dependence than modern thermopile pyranometers and less stability of the calibration. [5] The errors of photodiode pyranometers, which are probably most complex to correct, stem from the photodiode's wavelength-dependent spectral response (SR). [6] The responsivity to broadband irradiance therefore depends on the solar spectrum. Deviations between the current spectrum and the spectrum used for calibration will hence cause measurement errors, the so-called spectral error. This error depends on the temperature-dependent SR of the pyranometer, the air mass (AM), and the atmospheric conditions at the site at the time of measurement.The correction factors and calibration of rotating shadowband irradiometers (RSIs) are discussed in Section 2 and the uncertainty of photodiode pyranometer measurements is discussed in Section 3. The calculation method for the uncertainty of GHI, DNI, and DHI is presented in Section 4, first regarding the spectral uncertainty with respect to uncorrected and corrected measurements and then regarding further uncertainty contributions. In Section 5, the validation of the method is presented with the application of the method at the six measurement stations with RSI and reference data in different climates. Finally, conclusions are presented and summarized.

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Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

Cited by 9 publications

References 9 publications

Sunshape measurements with conventional rotating shadowband irradiometers

Sunshape measurements with conventional rotating shadowband irradiometers

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

Uncertainty Calculation Method for Photodiode Pyranometers

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