Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Forstinger, Anne; Wilbert, Stefan; Driesse, Anton; Hanrieder, Natalie; Affolter, Roman; Kumar, Santosh; Goswami, N. J.; Geuder, Norbert; Vignola, Frank; Zarzalejo, Luis F.; Habte, Aron

doi:10.1127/metz/2019/0972

Cited by 5 publications

(7 citation statements)

References 18 publications

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“…Then the RSI measurements obtained later in a resource assessment station could be described by nominal correction functions and estimated or measured spectra. A similar approach using a calibration period of several weeks was tested in Forstinger et al (2020), but it is still not applied for solar projects. Because of the possible variations between the spectral response of different pyranometers of the same model, using separate calibration constants for at least two of the three components (GHI, DHI, and DNI) is recommended; however, some RSI calibration methods include only GHI calibration.…”

Section: Calibration Methods For Rotating Shadowband Irradiometersmentioning

confidence: 99%

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

Sengupta

Habte

Wilbert

et al. 2021

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Section: Calibration Methods For Rotating Shadowband Irradiometersmentioning

confidence: 99%

“…Another set of correction functions was later presented in Geuder et al (2011). Additional new correction methods are on their way Forstinger et al 2020). An overview of RSI correction functions can be found in Jessen et al (2017).…”

Section: Correction Functions For Rotating Shadowband Irradiometersmentioning

confidence: 99%

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

Sengupta

Habte

Wilbert

et al. 2021

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“…Note that the increase in the photodiode sensitivity with increasing temperature is included in this calculation as the SR curve is partly shifted upward. [ 12 ]…”

Section: Uncertainty Calculation Methodsmentioning

confidence: 99%

“…The correction functions were further developed for RSIs (Figure 1), which typically use silicon photodiode pyranometers. [10][11][12][13] RSIs measure GHI and diffuse horizontal irradiance (DHI) so that direct normal irradiance (DNI) can be calculated using the solar zenith angle. In this case, corrections are also applied for DHI and DNI by utilization of the initial DHI and DNI values or the GHI and DHI are corrected first and then the DNI is calculated.…”

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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“…The method was developed in 2003 and based on global, diffuse, and direct irradiance [15]. Forstinger et al [16] suggested a new correction and calibration method based on a physical approach. The method aimed to remove the systematic errors and is based on information of the sensor properties, which includes its directional response and the site's atmospheric conditions.…”

Section: Introductionmentioning

confidence: 99%

Improving the Irradiance Data Measured by Silicon-Based Sensors

2021

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Silicon-based sensors are widely used for monitoring solar irradiance, in particular, in the field of Photovoltaic (PV) applications. We present a method to correct the global horizontal irradiance measured by silicon-based sensors that reduces the difference to the standard thermopile sensor measurements. A major motivation to use silicon-based sensors for the measurements of irradiance is their lower cost. In addition, their response time is much lower, and their spectral response is much closer to that of the PV systems. The analysis of the differences is based on evaluating four parameters that influence the sensor measurements, namely the temperature, cosine error, spectral mismatch, and calibration factor. Based on the analysis, a correction model is applied to the silicon sensors measurements. The model separates measurements under a clear sky and cloudy sky by combining the clearness index and the solar zenith angle. By applying the correction model on the measurements of the silicon-based sensor, the differences between sensor readings have been reduced significantly. The relative root mean squared difference (rRMSD) between the daily solar irradiation measured by both sensors decreased from 10.6% to 5.4% after applying the correction model, while relative mean absolute difference (rMAD) decreased from 7.4% to 2.5%. The difference in total annual irradiation decreased from 70 KWh/m2 (6.5%) to 15 kWh/m2 (1.5%) by the correction. The presented correction method shows promising results for a further improvement in the accuracy of silicon-based sensors.

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Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Cited by 5 publications

References 18 publications

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

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

Uncertainty Calculation Method for Photodiode Pyranometers

Improving the Irradiance Data Measured by Silicon-Based Sensors

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