Validation of an all‐sky imager–based nowcasting system for industrial <scp>PV</scp> plants

Kuhn, Pascal Moritz; Nouri, Bijan; Wilbert, Stefan; Prahl, Christoph; Kozonek, Nora; Schmidt, Thomas; Yasser, Zeyad; Ramírez, Lourdes; Zarzalejo, Luis F.; Meyer, Angela; Vuilleumier, Laurent; Heinemann, Detlev; Blanc, Philippe; Pitz‐Paal, Robert

doi:10.1002/pip.2968

Cited by 65 publications

(51 citation statements)

References 34 publications

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“…For practical reasons, a look-up table (LUT) for a range of temperatures and IWV was generated, which was then used to compute the reference clear-sky radiance distribution for every single image taken by the camera. A similar approach that is used to detect cloud patterns is described in Bertin et al (2015a) and Liandrat et al (2017).…”

Section: Thermal Infrared Cloud Cameramentioning

confidence: 99%

“…The Sky Insight cloud imager is sensitive in the 8-13 µm wavelength range and gives cloud information of the whole of the upper hemisphere. Their system is mainly used for cloud cover forecasts up to 30 min in advance, which is relevant for global horizontal irradiance forecasts or optical communication link availability (Bertin et al, 2015a;Liandrat et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Final response to RC2

Aebi¹

2018

Preprint

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The thermal infrared cloud camera (IRCCAM) is a prototype instrument that determines cloud fraction continuously during daytime and night-time using measurements of the absolute thermal sky radiance distributions in the 8-14 µm wavelength range in conjunction with clear-sky radiative transfer modelling. Over a time period of 2 years, the fractional cloud coverage obtained by the IRCCAM is compared with two commercial cameras (Mobotix Q24M and Schreder VIS-J1006) sensitive in the visible spectrum, as well as with the automated partial cloud amount detection algorithm (APCADA) using pyrgeometer data. Over the 2-year period, the cloud fractions determined by the IRCCAM and the visible all-sky cameras are consistent to within 2 oktas (0.25 cloud fraction) for 90 % of the data set during the day, while for day-and night-time data the comparison with the APCADA algorithm yields an agreement of 80 %. These results are independent of cloud types with the exception of thin cirrus clouds, which are not detected as consistently by the current cloud algorithm of the IRCCAM. The measured absolute sky radiance distributions also provide the potential for future applications by being combined with ancillary meteorological data from radiosondes and ceilometers.Published by Copernicus Publications on behalf of the European Geosciences Union.

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Section: Thermal Infrared Cloud Cameramentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Final response to RC2

Aebi¹

2018

Preprint

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“…The root mean square deviation (RMSD) and the mean absolute deviation (MAD) are often used as error metrics for nowcasting systems (e.g., [18][19][20][21][22]). The mentioned studies use validation periods from 15 days to six months.…”

Section: Introductionmentioning

confidence: 99%

“…For a real-time application, the methodology must be capable in determining appropriate uncertainties under all possible ambient conditions. The used nowcasting system itself had been benchmarked in previous publications [22,24]. In our study, the basis are DNI nowcasts, but the same approach can be applied for nowcasting global horizontal irradiance (GHI) or global tilted irradiance (GTI).…”

Section: Introductionmentioning

confidence: 99%

Real-Time Uncertainty Specification of All Sky Imager Derived Irradiance Nowcasts

Nouri¹,

Wilbert²,

Kuhn³

et al. 2019

Remote Sensing

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The incoming downward shortwave solar irradiance is harvested to an increasing extent by solar power plants. However, the variable nature of this energy source poses an operational challenge for solar power plants and electrical grids. Intra hour solar irradiance nowcasts with a high temporal and spatial resolution could be used to tackle this challenge. All sky imager (ASI) based nowcasting systems fulfill the requirements in terms of temporal and spatial resolution. However, ASI nowcasts can only be used if the required accuracies for applications in solar power plants and electrical grids are fulfilled. Scalar error metrics, such as mean absolute deviation, root mean square deviation, and skill score are commonly used to estimate the accuracy of nowcasting systems. However, these overall error metrics represented by a single number per metric are neither suitable to determine the real time accuracy of a nowcasting system in the actual weather situation, nor suitable to describe any spatially resolved nowcast accuracy. The performance of ASI-based nowcasting systems is strongly related to the prevailing weather conditions. Depending on weather conditions, large discrepancies between the overall and current system uncertainties are conceivable. Furthermore, the nowcast accuracy varies strongly within the irradiance map as higher errors may occur at transient zones close to cloud shadow edges. In this paper, we present a novel approach for the spatially resolved real-time uncertainty specification of ASI-based nowcasting systems. The current irradiance conditions are classified in one of eight distinct temporal direct normal irradiance (DNI) variability classes. For each class and lead-time, an upper and lower uncertainty value is derived from historical data, which describes a coverage probability of 68.3%. This database of uncertainty values is based on deviations of the irradiance maps, compared to three reference pyrheliometers in Tabernas, Andalucia over two years (2016 and 2017). Increased uncertainties due to transient effects are considered by detecting transient zones close to cloud shadow edges within the DNI map. The width of the transient zones is estimated by the current average cloud height, cloud speed, lead-time, and Sun position. The final spatially resolved uncertainties are validated with three reference pyrheliometers, using a data set consisting of the entire year 2018. Furthermore, we developed a procedure based on the DNI temporal variability classes to estimate the expected average uncertainties of the nowcasting system at any geographical location. The novel method can also be applied for global tilted or horizontal irradiance and is assumed to improve the applicability of the ASI nowcasts.

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“…Very short term forecasts, e.g. for the next 15 min, can be provided by camera based nowcasting systems (Chow et al, 2011;Kuhn et al, 2017b).…”

Section: Introductionmentioning

confidence: 99%

Applications of a shadow camera system for energy meteorology

Kuhn¹,

Wilbert²,

Prahl³

et al. 2018

Adv. Sci. Res.

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Abstract. Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.

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Validation of an all‐sky imager–based nowcasting system for industrial PV plants

Cited by 65 publications

References 34 publications

Final response to RC2

Final response to RC2

Real-Time Uncertainty Specification of All Sky Imager Derived Irradiance Nowcasts

Applications of a shadow camera system for energy meteorology

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