• Energy Research

Abstract The demand for accurate solar irradiance nowcast increases together with the rapidly growing share of solar energy within our electricity grids. Intra-hour variabilities, mainly caused by clouds, have a significant impact on solar power plant dispatch and thus on electricity grids. All sky imager (ASI) based nowcasting systems, with a high temporal and spatial resolution, can provide irradiance nowcasts that can help to optimize CSP plant operation, solar power plant dispatch and grid operation. The radiative effect of clouds is highly variable and depends on micro- and macrophysical cloud properties. Frequently, nowcasting systems have to measure/estimate the radiative effect during complex multi-layer conditions with strong variations of the optical properties between individual clouds. We present a novel approach determining cloud transmittance from measurements or from correlations of transmittance with cloud height information. The cloud transmittance is measured by a pyrheliometer when shaded, as the ratio of shaded direct normal irradiance (DNI) and clear sky DNI. However, for most clouds, direct transmittance measurements are not available, as these clouds are not shading the used pyrheliometers. These clouds receive an estimated transmittance value based on (1) their height, (2) results of a probability analysis with historical cloud height and transmittance measurements as well as (3) recent transmittance measurements and their corresponding cloud height. Cloud heights are measured by a stereoscopic approach utilizing two ASIs. We discuss site dependencies of the presented transmittance estimation method and the potential integration of automatic cloud classification approaches. We validated the cloud transmittance estimation over two years (2016 and 2017) and compare the probabilistic cloud transmittance estimation approach with four simple approaches. The overall mean-absolute deviation (MAD) and root-mean-square deviation (RMSD) are 0.11 and 0.16 respectively for transmittance. The deviations are significantly lower for optically thick or thin clouds and larger for clouds with moderate transmittance between 0.18 and 0.585. Furthermore we validated the overall DNI forecast quality of the entire nowcasting system, using this transmittance estimation method, over the same data set with three spatially distributed pyrheliometers. Overall deviations of 13% and 21% are reached for the relative MAD and RMSD with a lead time of 10 min. The effects of the chosen data set on the validation results are demonstrated by means of the skill score.

Highly spatially and temporally resolved solar irradiance maps are of special interest for predicting ramp rates and for optimizing operations in solar power plants. Irradiance maps with lead times between 0 and up to 30 min can be generated using all-sky imager based nowcasting systems or with shadow camera systems. Shadow cameras provide photos of the ground taken from an elevated position below the clouds. In this publication, we present a shadow camera system, which provides spatially resolved Direct Normal Irradiance (DNI), Global Horizontal Irradiance (GHI) and Global Tilted Irradiance (GTI) maps. To the best of our knowledge, this is the first time a shadow camera system is achieved. Its generated irradiance maps have two purposes: (1) The shadow camera system is already used to derive spatial averages to benchmark all-sky imager based nowcasting systems. (2) Shadow camera systems can potentially provide spatial irradiance maps for plant operations and may act as nowcasting systems. The presented shadow camera system consists of six cameras taking photos from the top of an 87 m tower and is located at the Plataforma Solar de Almeria in southern Spain. Out of six photos, an ortho-normalized image (orthoimage) is calculated. The orthoimage under evaluation is compared with two reference orthoimages. Out of the three orthoimages and one additional pyranometer and pyrheliometer, spatially resolved irradiance maps (DNI, GHI, GTI) are derived. In contrast to satellites, the shadow camera system uses shadows to obtain irradiance maps and achieves higher spatial and temporal resolutions. he preliminary validation of the shadow camera system, conducted in detail on two example days (2015-09-18, 2015-09-19) with 911 one-minute averages, shows deviations between 4.2% and 16.7% root mean squared errors (RMSE), 1.6% and 7.5% mean absolute errors (MAE) and standard deviations between 4.2% and 15.4% for DNI maps calculated with the derived approach. The GHI maps show deviations below 10% RMSE, between 2.1% and 7.1% MAE and standard deviations between 3.2% and 7.9%. Three more days (2016-05-11, 2016-09-01, 2016-12-09) are evaluated, briefly presented and show similar deviations. These deviations are similar or below all-sky imager based nowcasts for lead time zero minutes. The deviations are small for photometrically uncalibrated, low-cost and off-the-shelf surveillance cameras, which is achieved by a segmentation approach.

Reference solar irradiance spectra are needed to specify key parameters of solar technologies such as photovoltaic cell efficiency, in a comparable way. The IEC 60904-3 and ASTM G173 standards present such spectra for Direct Normal Irradiance (DNI) and Global Tilted Irradiance (GTI) on a 37° tilted sun-facing surface for one set of clear-sky conditions with an air mass of 1.5 and low aerosol content. The IEC/G173 standard spectra are the widely accepted references for these purposes. Hence, the authors support the future replacement of the outdated ISO 9845 spectra with the IEC spectra within the ongoing update of this ISO standard. The use of a single reference spectrum per component of irradiance is important for clarity when comparing and rating solar devices such as PV cells. However, at some locations the average spectra can differ strongly from those defined in the IEC/G173 standards due to widely different atmospheric conditions and collector tilt angles. Therefore, additional subordinate standard spectra for other atmospheric conditions and tilt angles are of interest for a rough comparison of product performance under representative field conditions, in addition to using the main standard spectrum for product certification under standard test conditions. This simplifies the product selection for solar power systems when a fully-detailed performance analysis is not feasible (e.g. small installations). Also, the effort for a detailed yield analyses can be reduced by decreasing the number of initial product options. After appropriate testing, this contribution suggests a number of additional spectra related to eight sets of atmospheric conditions and tilt angles that are currently considered within ASTM and ISO working groups. The additional spectra, called subordinate standard spectra, are motivated by significant spectral mismatches compared to the IEC/G173 spectra (up to 6.5%, for PV at 37° tilt and 10–15% for CPV). These mismatches correspond to potential accuracy improvements for a quick estimation of the average efficiency by applying the appropriate subordinate standard spectrum instead of the IEC/G173 spectra. The applicability of these spectra for PV performance analyses is confirmed at five test sites, for which subordinate spectra could be intuitively selected based on the average atmospheric aerosol optical depth (AOD) and precipitable water vapor at those locations. The development of subordinate standard spectra for DNI and concentrating solar power (CSP) and concentrating PV (CPV) is also considered. However, it is found that many more sets of atmospheric conditions would be required to allow the intuitive selection of DNI spectra for the five test sites, due in particular to the stronger effect of AOD on DNI compared to GTI. The matrix of subordinate GTI spectra described in this paper are recommended to appear as an option in the annex of future standards, in addition to the obligatory use of the main spectrum from the ASTM G173 and IEC 60904 standards.

In solar tower plants, radiation losses between the heliostat field and the receiver occur due to atmospheric extinction which varies with site and time. Currently, atmospheric extinction is usually approximated using a few constant standard atmospheric conditions in ray-tracing and plant optimization tools. Some tools allow the input of time dependent extinction data, but such site specific data sets are generally not available for prospective concentrated solar power (CSP) sites. In this paper, the most applied model equations which are implemented in different ray-tracing tools are summarized and compared. Several developed approaches to determine atmospheric extinction are presented. Furthermore, different studies about the effect of atmospheric extinction on the tower plant yield are summarized. It can be concluded that project developers should consider atmospheric extinction and its temporal variation as site specific data sets in power plant optimization, plant yield forecast and plant operation. The effect of atmospheric extinction can account for a reduction of the annual plant yield of up to several percent points and is dependent on the heliostat field size, the operation strategy and the on-site atmospheric conditions. Different approaches to determine atmospheric extinction for solar tower plants at a future CSP site have been developed and validated in the past and can be applied dependent on the prevailing atmospheric conditions. The costs of a power plant can be lowered by reducing the simulation uncertainty since it implies in turn a reduction of risk margins in plant yield forecasts.

Abstract Reference solar irradiance spectra are needed to specify key parameters of solar technologies such as photovoltaic cell efficiency, in a comparable way. The IEC 60904-3 and ASTM G173 standards present such spectra for Direct Normal Irradiance (DNI) and Global Tilted Irradiance (GTI) on a 37° tilted sun-facing surface for one set of clear-sky conditions with an air mass of 1.5 and low aerosol content. The IEC/G173 standard spectra are the widely accepted references for these purposes. Hence, the authors support the future replacement of the outdated ISO 9845 spectra with the IEC spectra within the ongoing update of this ISO standard. The use of a single reference spectrum per component of irradiance is important for clarity when comparing and rating solar devices such as PV cells. However, at some locations the average spectra can differ strongly from those defined in the IEC/G173 standards due to widely different atmospheric conditions and collector tilt angles. Therefore, additional subordinate standard spectra for other atmospheric conditions and tilt angles are of interest for a rough comparison of product performance under representative field conditions, in addition to using the main standard spectrum for product certification under standard test conditions. This simplifies the product selection for solar power systems when a fully-detailed performance analysis is not feasible (e.g. small installations). Also, the effort for a detailed yield analyses can be reduced by decreasing the number of initial product options. After appropriate testing, this contribution suggests a number of additional spectra related to eight sets of atmospheric conditions and tilt angles that are currently considered within ASTM and ISO working groups. The additional spectra, called subordinate standard spectra, are motivated by significant spectral mismatches compared to the IEC/G173 spectra (up to 6.5%, for PV at 37° tilt and 10–15% for CPV). These mismatches correspond to potential accuracy improvements for a quick estimation of the average efficiency by applying the appropriate subordinate standard spectrum instead of the IEC/G173 spectra. The applicability of these spectra for PV performance analyses is confirmed at five test sites, for which subordinate spectra could be intuitively selected based on the average atmospheric aerosol optical depth (AOD) and precipitable water vapor at those locations. The development of subordinate standard spectra for DNI and concentrating solar power (CSP) and concentrating PV (CPV) is also considered. However, it is found that many more sets of atmospheric conditions would be required to allow the intuitive selection of DNI spectra for the five test sites, due in particular to the stronger effect of AOD on DNI compared to GTI. The matrix of subordinate GTI spectra described in this paper are recommended to appear as an option in the annex of future standards, in addition to the obligatory use of the main spectrum from the ASTM G173 and IEC 60904 standards.