Soiling of irradiation sensors and methods for soiling correction

Geuder, Norbert; Quaschning, Volker

doi:10.1016/j.solener.2006.06.001

Cited by 37 publications

(21 citation statements)

References 10 publications

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“…We hence assume DNI Ref = 0.9 % for the standard uncertainty. Additionally, an uncertainty due to pyrheliometer soiling of Soil ≈ 0.2 % can be estimated in respect of the findings in Geuder and Quaschning (2006). The calibration error can have a systematic component.…”

Section: Recommendations For Dlr2008 Calibration Durationmentioning

confidence: 93%

“…Among other tests, the quality check tests and marks if measured values are physically possible, if their fluctuation (or lack of it) is realistic and if the data points have been manually flagged/commented during the measuring period. Furthermore, a soiling correction algorithm is applied to DNI Ref in accordance to the documented cleaning events following the method from Geuder and Quaschning (2006). Then, the LI-COR calibration factor CF Licor is applied to the RSI data.…”

Section: Calibration Methods Dlr2008mentioning

confidence: 99%

“…These ground measurements can be obtained by solar trackers and pyrheliometers or by rotating shadowband irradiometers (RSIs). Due to their lower susceptibility to soiling, RSIs have an important advantage over thermopile pyrheliometers during long-term deployment in remote and inaccessible sites, where daily cleaning of the instrument's aperture is not possible (Geuder and Quaschning, 2006;Pape et al, 2009;Maxwell et al, 1999). RSIs are also advantageous in terms of installation and maintenance costs and the typically achieved data availability.…”

Section: Introductionmentioning

confidence: 99%

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Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

Jessen

Wilbert²,

Nouri³

et al. 2016

Atmos. Meas. Tech.

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Abstract. Resource assessment for concentrated solar power (CSP) needs accurate direct normal irradiance (DNI) measurements. An option for such measurement campaigns is the use of thoroughly calibrated rotating shadowband irradiometers (RSIs). Calibration of RSIs and Si-sensors is complex because of the inhomogeneous spectral response of these sensors and incorporates the use of several correction functions. One calibration for a given atmospheric condition and air mass might not be suitable under different conditions. This paper covers procedures and requirements of two calibration methods for the calibration of rotating shadowband irradiometers. The necessary duration of acquisition of test measurements is examined with regard to the site-specific conditions at Plataforma Solar de Almería (PSA) in Spain. Seven data sets of long-term test measurements were collected. For each data set, calibration results of varying durations were compared to its respective long-term result. Our findings show that seasonal changes of environmental conditions are causing small but noticeable fluctuation of calibration results. Calibration results within certain periods (i.e. November to January and April to May) show a higher likelihood of deviation. These effects can partially be attenuated by including more measurements from outside these periods.Consequently, the duration of calibrations at PSA can now be selected depending on the time of year in which measurements commence.

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Section: Recommendations For Dlr2008 Calibration Durationmentioning

confidence: 93%

Section: Calibration Methods Dlr2008mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

Jessen

Wilbert²,

Nouri³

et al. 2016

Atmos. Meas. Tech.

View full text Add to dashboard Cite

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“…The latter can be improved by daily cleaning which is of high importance. This is necessary particularly at sites with pyrheliometers measuring the DNI as they are more sensitive for soiling than RSIs due to their clear optics and scattering losses in the instrument [7][8][9]. The DNI sensor soiling has been evaluated trying to cover one complete year starting in July 2014.…”

Section: Sensor Soilingmentioning

confidence: 99%

The enerMENA meteorological network – Solar radiation measurements in the MENA region

Schüler¹,

Wilbert²,

Geuder

et al. 2016

AIP Conference Proceedings

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Abstract. For solar resource assessment of solar power plants and adjustment of satellite data, high accuracy measurement data of irradiance and ancillary meteorological data is needed. For the MENA region (Middle East and Northern Africa), which is of high importance for concentrating solar power applications, so far merely 2 publicly available ground measurement stations existed (BSRN network). This gap has been filled by ten stations in Morocco, Algeria, Tunisia, Egypt and Jordan. In this publication the data quality is analyzed by evaluating data completeness and the cleanliness of irradiance sensors in comparison for all of the stations. The pyrheliometers have an average cleanliness of 99.2 % for week-daily cleaning. This is a 5 times higher effort than for Rotating Shadowband Irradiometer (RSI) stations which even have a slightly higher average cleanliness of 99.3 % for weekly cleaning. Furthermore, RSI stations show a data completeness of 99.4 % compared to 93.6 % at the stations equipped with thermal sensors. The results of this analysis are used to derive conclusions concerning instrument choice and are hence also applicable to other solar radiation measurements outside the enerMENA network. It turns out that RSIs are the more reliable and robust choice in cases of high soiling, rare station visits for cleaning and maintenance, as usual in desert sites. Furthermore, annual direct normal and global horizontal irradiation as well as average meteorological parameters are calculated for all of the stations.

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“…For CMP21 and CM22 sensors used in ARAD these numbers are < 10 W m −2 and < 5 W m −2 , respectively. Influence of soiling effects (excluding e.g., soiling by birds) is generally anticipated to be larger for pyrheliometers than for pyranometers (due to collimation) (Geuder and Quaschning, 2006;Michalsky et al, 1988;Myers et al, 2001). Following the results of Vuilleumier et al (2014) the effect of soiling should be well below the 1 % level for regularly maintained instruments (i.e., cleaning performed at least several times a week).…”

Section: Shortwave Fluxesmentioning

confidence: 99%

The Austrian radiation monitoring network ARAD – best practice and added value

et al. 2016

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Abstract. The Austrian RADiation monitoring network (ARAD) has been established to advance the national climate monitoring and to support satellite retrieval, atmospheric modeling and the development of solar energy techniques. Measurements cover the downward solar and thermal infrared radiation using instruments according to Baseline Surface Radiation Network (BSRN) standards. A unique feature of ARAD is its vertical dimension of five stations, covering an altitude range between about 200 m a.s.l (Vienna) and 3100 m a.s.l. (BSRN site Sonnblick). The paper outlines the aims and scopes of ARAD, its measurement and calibration standards, methods, strategies and station locations. ARAD network operation uses innovative data processing for quality assurance and quality control, utilizing manual and automated control algorithms. A combined uncertainty estimate for the broadband shortwave radiation fluxes at all five ARAD stations, using the methodology specified by the Guide to the Expression of Uncertainty in Measurement indicates that relative accuracies range from 1.5 to 2.9 % for large signals (global, direct: 1000 W m −2 , diffuse: 500 W m −2 ) and from 1.7 to 23 % (or 0.9 to 11.5 W m −2 ) for small signals (50 W m −2 ) (expanded uncertainties corresponding to the 95 % confidence level). If the directional response error of the pyranometers and the temperature response of the instruments and the data acquisition system (DAQ) are corrected, this expanded uncertainty reduces to 1.4 to 2.8 % for large signals and to 1.7 to 5.2 % (or 0.9-2.6 W m −2 ) for small signals. Thus, for large signals of global and diffuse radiation, BSRN target accuracies are met or nearly met (missed by less than 0.2 percentage points, pps) for 70 % of the ARAD measurements after this correction. For small signals of direct radiation, BSRN targets are achieved at two sites and nearly met (also missed by less than 0.2 pps) at the other sites. For small signals of global and diffuse radiation, targets are achieved at all stations. Additional accuracy gains can be achieved in the future through additional measurements, corrections and a further upgrade of the DAQ. However, to improve the accuracy of measurements of direct solar radiation, improved instrument accuracy is needed. ARAD could serve as a useful example for establishing state-of-the-art radiation monitoring at the national level with a multiple-purpose approach. Instrumentation, guidelines and tools (such as the data quality control) developed within ARAD are intended to increase monitoring capabilities of global radiation and thus designed to allow straightforward adoption in other regions, without high development costs.

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Soiling of irradiation sensors and methods for soiling correction

Cited by 37 publications

References 10 publications

Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

Calibration methods for rotating shadowband irradiometers and optimizing the calibration duration

The enerMENA meteorological network – Solar radiation measurements in the MENA region

The Austrian radiation monitoring network ARAD – best practice and added value

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