Irradiance and cloud optical properties from photovoltaic power data

<p class="western" align="justify">The rapid increase in solar photovoltaic (PV) installations worldwide has resulted in the electricity grid becoming increasingly dependent on atmospheric conditions, thus requiring more accurate forecasts of incoming solar irradiance. In this context, measured data from PV systems are a valuable source of information about the optical properties of the atmosphere, in particular the cloud optical depth (COD). This work reports first results from an inversion algorithm developed to infer global, direct and diffuse irradiance as well as atmospheric optical properties from PV power measurements, with the goal of assimilating this information into numerical weather prediction (NWP) models.</p> <p class="western" align="justify">High resolution measurements from both PV systems and pyranometers were collected as part of the BMWi-funded MetPVNet project, in the Allgäu region during autumn 2018 and summer 2019. These data were then used together with a PV model and both the DISORT and MYSTIC radiative transfer schemes within libRadtran (Emde et al., 2016; Mayer and Kylling, 2005)⁠ to infer cloud optical depth as well as direct, diffuse and global irradiance under highly variable atmospheric conditions. Hourly averages of each of the retrieved quantities were compared with the corresponding predictions of the COSMO weather model as well as data from satellite retrievals, and periods with differing degrees of variability and different cloud types were analysed. The DISORT-based algorithm is able to accurately retrieve COD, direct and diffuse irradiance components as long as the cloud fraction is high enough, whereas under broken cloud conditions the presence of 3D effects can lead to large errors. In that case the global horizontal irradiance is derived from tilted irradiance measurements and/or PV data using a lookup table based on the MYSTIC 3D Monte Carlo radiative transfer solver (Mayer, 2009)⁠. This work will provide the basis for future investigations using a larger number of PV systems to evaluate the improvements to irradiance and power forecasts that could be achieved by the assimilation of inferred irradiance into an NWP model.</p> <p class="western"><strong>References</strong></p> <p class="western">Emde, C., Buras-Schnell, R., Kylling, A., Mayer, B., Gasteiger, J., Hamann, U., Kylling, J., Richter, B., Pause, C., Dowling, T. and Bugliaro, L.: The libRadtran software package for radiative transfer calculations (version 2.0.1), Geosci. Model Dev., 9(5), 1647–1672, doi:10.5194/gmd-9-1647-2016, 2016.</p> <p class="western">Mayer, B.: Radiative transfer in the cloudy atmosphere, EPJ Web Conf., 1, 75–99, doi:10.1140/epjconf/e2009-00912-1, 2009.</p> <p class="western">Mayer, B. and Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations - description and examples of use, Atmos. Chem. Phys., 5(7), 1855–1877, doi:10.5194/acp-5-1855-2005, 2005.</p>

Global and diffuse solar radiant exposures at Pone

Radiation measurements are being carried out at Pune since 1957. The radiation data for the period 1986-90 are studied here with reference to general sky condition and rainfall distribution. Global irradiances show a decrease of about 5 per cent over the last four decades, The diffuse irradiation contributes about 23 per cent to the global irradiance during winter months, Its proportion increases to more than 70 per cent during the monsoon period. The specific rainfall distribution affects both global and diffuse irradiances but in opposite directions, The diffuse irradiance shows increases as the atmospheric transmission decreases, However, the changes found have not become statistically highly significant as yet.

Above-aircraft cirrus cloud and aerosol optical depth from hyperspectral irradiances measured by a total-diffuse radiometer

This study develops the use of spectral total and diffuse irradiance measurements, made from a prototype hyperspectral total-diffuse Sunshine Pyranometer (SPN-S), to retrieve layer fine-mode aerosol (τaer) and total optical depths from airborne platforms. Additionally, we use spectral analysis in an attempt to partition the total optical depth it into its τaer and cirrus cloud optical depth (τcld) components in the absence of coarse-mode aerosols. Two retrieval methods are developed: one leveraging information in the diffuse irradiance, and the other using spectral characteristics of the transmitted direct beam, with each approach best suited for specific cloud and aerosol conditions. SPN-S has advantages over traditional sun-photometer systems including no moving parts and a low cost. However, a significant drawback of the instrument is that it is unable to measure the direct beam irradiance as accurately as sun-photometers. To compensate for the greater measurement uncertainty of the radiometric irradiances these retrieval techniques employ ratioed inputs or spectral information to reduce output uncertainty. This analysis uses irradiance measurements from SPN-S and the Solar Spectral Flux Radiometer (SSFR) aboard the National Aeronautics and Space Administration’s (NASA) P-3 aircraft during the 2018 deployment of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign and the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission to quantify above-aircraft cirrus τcld and derive vertical profiles of layer τaer. Validation of the τaer retrieval is accomplished by comparison with collocated measurements of direct solar irradiance made by the Sky-Scanning Sun-Tracking Atmospheric Research (4STAR) and in situ measurements of aerosol optical depth. For the aggregated 2018 ORACLES results, regression between the SPN-S based method and sun-photometer τaer values yield a slope of 0.96 with an R2 of 0.96, while the root-mean-square error (RMSE) is 3.0 × 10−2. When comparing the retrieved τaer to profiles of integrated in situ measurements of optical extinction, the slope, R2, and RMSE values for ORACLES are 0.90, 0.96, 3.4 × 10−2, and for CAMP2Ex are 0.94, 0.97, 3.4 × 10−2 respectively. This paper is a demonstration of methods for deriving cloud and aerosol optical properties in environments where both atmospheric constituents may be present. With improvements to the low-cost SPN-S radiometer instrument, it may be possible to extend these methods to a broader set of sampling applications, such as ground-based settings.

An Operational Radiometric Correction Technique for Shadow Reduction in Multispectral UAV Imagery

This study focuses on the recovery of information from shadowed pixels in RGB or multispectral imagery sensed from unmanned aerial vehicles (UAVs). The proposed technique is based on the concept that a property characterizing a given surface is its spectral reflectance, i.e., the ratio between the flux reflected by the surface and the radiant flux received by the surface, and this ratio is usually similar under direct-plus-diffuse irradiance and under diffuse irradiance when a Lambertian behavior can be assumed. Scene-dependent elements, such as trees, shrubs, man-made constructions, or terrain relief, can block part of the direct irradiance (usually sunbeams), in which part of the surface only receives diffuse irradiance. As a consequence, shadowed surfaces comprising pixels of the image created by the UAV remote sensor appear. Regardless of whether the imagery is analyzed by means of photointerpretation or digital classification methods, when the objective is to create land cover maps, it is hard to treat these areas in a coherent way in terms of the areas receiving direct and diffuse irradiance. The hypothesis of the present work is that the relationship between irradiance conditions in shadowed areas and non-shadowed areas can be determined by following classical empirical line techniques for fulfilling the objective of a coherent treatment in both kinds of areas. The novelty of the presented method relies on the simultaneous recovery of information in non-shadowed and shadowed areas by the in situ spectral reflectance measurements of characterized Lambertian targets followed by smoothing of the penumbra area. Once in the lab, firstly, we accurately detected the shadowed pixels by combining two well-known techniques for the detection of the shadowed areas: (1) using a physical approach based on the sun’s position and the digital surface model of the area covered by the imagery; and (2) the image-based approach using the histogram properties of the intensity image. In this paper, we present the benefits of the combined usage of both techniques. Secondly, we applied a fit between non-shadowed and shadowed areas by using a twin set of spectrally characterized target sets. One set was placed under direct and diffuse irradiance (non-shadowed targets), whereas the second set (with the same spectral characteristics) was placed under diffuse irradiance (shadowed targets). Assuming that the reflectance of the homologous targets of each set was the same, we approximated the diffuse incoming irradiance through an empirical line correction. The model was applied to all detected shadowed areas in the whole scene. Finally, a smoothing filter was applied to the penumbra transitions. The presented empirical method allowed the operational and coherent recovery of information from shadowed areas, which is very common in high-resolution UAV imagery.