Spatial turn / Raumforschung

Zweitveröffentlichun

High resolution short-term solar forecasting for the integration of PV in Energy Systems

The high resolution of the Eye2Sky network allows very short-term forecasting of cloud cover, solar irradiance and PV power output. For that purpose, advanced image analysis, cloud tracking and modelling merges multiple ASI sky and cloud observations into maps of solar irradiance

Cloud Shadows in Satellite-based Solar Irradiance Estimation: Improved Correction using EUMETSAT's Cloud Top Height Data

The estimation of solar surface irradiance at high spatio-temporal resolution from geo-stationary satellite images is a well-established technique, for example by using the Heliosat method. The method has widely reduced the need for expensive ground measurements, especially in remote regions. However, the location of cloud shadows at the ground is difficult to determine and thus a significant source of errors when either the distance from the sub-satellite point or the cloud top height (CTH) increases. Although several methods have been proposed in the literature to reduce these errors, it is still an issue. We present a novel approach to correct the cloud shadow location based on the satellite-cloud-sun geometry using the CTH maps from the EUMETSAT data archive. It uses satellite viewing angles and solar position angles to determine the correct cloud shadow location for each cloudy pixel. The method is tested on cloud index (CI) maps for the months of July, August and September 2018 derived by applying the Heliosat method on the 0.6 um visible channel images from Meteosat-8 located at 41.5°E. Convective clouds with large CTHs are frequently observed over the Indian subcontinent in these three months due to the Indian summer monsoon. The global horizontal solar irradiance (GHI) obtained from the corrected CI image is validated at two BSRN stations. The normalized root mean square error (nRMSE) is reduced from 23.2% to 20.9% for the Gurgaon station and from 15.4% to 13.9% at Tiruvallur. In general, correcting the cloud shadow location on CI map improved the accuracy of the estimated GHI. Nonetheless, the method is sensitive to the accuracy of the CTH dataset and individual cases were found for which the correction reduced the accuracy

Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors

Intra-day forecasts of global horizontal solar irradiance (GHI) are widely produced by displacing existing clouds on a geo-stationary satellite image to their future locations with cloud motion vectors (CMVs) derived from preceding images. The CMV estimation methods assume rigid cloud bodies with advective motion, which performs reasonably well in mid-latitudes but can be strained for tropical and sub-tropical climatic zones during prolonged periods of seasonal convection. We study the impact of the South Asian monsoon time convection on the accuracy of CMV based forecasts by analysing 2 years of forecasts from three commonly used CMV methods—Block-match, Farnebäck (Optical flow) and TV-L1 (Optical flow). Forecasted cloud index (CI) maps of the entire image section are validated against analysis CI maps for the period 2018–2019 for forecast lead times from 0 to 5.5 h. Site-level GHI forecasts are validated against ground measured data from two Baseline Surface Radiation Network stations—Gurgaon (GUR) and Tiruvallur (TIR), located in hot semi-arid and tropical savanna climatic zones respectively. The inter-seasonal variation of forecast accuracy is prominent and a clear link is found between the increase in convection, represented by a decrease in outgoing longwave radiation (OLR), and the decrease in forecast accuracy. The GUR site shows the highest forecast error in the southwest monsoon period and exhibits a steep rise of forecast error with the increase in convection. The highest forecast error occurs in the northeast monsoon period of December in TIR. The impact of convection on the number of erroneous time blocks of predicted photovoltaic production is also studied. Our results provide insights into the contribution of convection to errors in CMV based forecasts and shows that OLR can be used as a feature in future forecasting methods to consider the impact of convection on forecast accuracy

Forecasting Solar Irradiance by looking at clouds from above and below

The energy meteorology measurement network Eye2Sky is a cloud monitoring system covering roughly 110x100 km in north-west Germany. It is equipped with 38 cloud cameras, solar radiation measurement stations and individual Lidar based cloud altitude measurements distributed throughout the region around Oldenburg. The system collects high-resolution information on solar radiation, tracks the variability at different locations and outputs forecasts for very short time scales. It covers a resolution range of fewer than 100 metres and less than 1 minute and supports forecasts of up to one hour (depending on the prevailing cloud height). A second data source for this region is given by images from the geostationary satellite MSG. With these images longer forecast horizons are achieved in a coarser resolution. The hybrid use of both data sources has only just begun in the community. This allows the development of new models with an improved quality of predictions. The presentation gives an overview on Helmholtz AI collaboration of DLR VE and AI collaboration with institutes DLR SP and DLR SF

DYNAMOS - Dynamik systemischer Effekte durch die Einspeisung erneuerbarer Energien: Hochfrequente Fluktuationen und deren Auswirkung auf den Abruf marktorientierter Systemdienstleistung

Dynamik systemischer Effekte durch die Einspeisung erneuerbarer Energien: Hochfrequente Fluktuationen und deren Auswirkung auf den Abruf marktorientierter Systemdienstleistung - Schlussbericht DLR-Institut für Vernetzte Energiesysteme - Projekt: DYNAMO

In vivo ligamentogenesis in embroidered poly(lactic-co-ε-caprolactone) / polylactic acid scaffolds functionalized by fluorination and hexamethylene diisocyanate cross-linked collagen foams

Although autografts represent the gold standard for anterior cruciate ligament (ACL) reconstruction, tissue-engineered ACLs provide a prospect to minimize donor site morbidity and limited graft availability. This study characterizes the ligamentogenesis in embroidered poly(L-lactide-co-epsilon-caprolactone) (P(LA-CL)) / polylactic acid (PLA) constructs using a dynamic nude mice xenograft model. (P(LA-CL))/PLA scaffolds remained either untreated (co) or were functionalized by gas fluorination (F), collagen foam cross-linked with hexamethylene diisocyanate (HMDI) (coll), or F combined with the foam (F+coll). Cell-free constructs or those seeded for 1 week with lapine ACL ligamentocytes were implanted into nude mice for 12 weeks. Following explantation, cell vitality and content, histo(patho)logy of scaffolds (including organs: liver, kidney, spleen), sulphated glycosaminoglycan (sGAG) contents and biomechanical properties were assessed. Scaffolds did not affect mice weight development and organs, indicating no organ toxicity. Moreover, scaffolds maintained their size and shape and reflected a high cell viability prior to and following implantation. Coll or F+coll scaffolds seeded with cells yielded superior macroscopic properties compared to the controls. Mild signs of inflammation (foreign-body giant cells and hyperemia) were limited to scaffolds without collagen. Microscopical score values and sGAG content did not differ significantly. Although remaining stable after explantation, elastic modulus, maximum force, tensile strength and strain at F-max were significantly lower in explanted scaffolds compared to those before implantation, with no significant differences between scaffold subtypes, except for a higher maximum force in F+coll compared with F samples (in vivo). Scaffold functionalization with fluorinated collagen foam provides a promising approach for ACL tissue engineering

High resolution hybrid forecast based on the combination of satellite and an all sky imager network forecasts

A method to combine a highly resolved All sky imager (ASI) network forecast with a satellite based forecast was developed. The ASI network forecast input is based on the data from the DLR's Eye2Sky network. This network is installed in NortWest Germany and includes 29 ASIs, 10 Rotating Shadowband Irradiometers (RSIs) and 2 reference meteorological stations (based on thermal irradiometers) in an extent of 100 km2. This forecast was developed by our colleges from DLR-SF (Publication in preparation). It has a forecast horizon of 30 minutes and a step of 1 min with an update of 30 seconds on a domain of 40 km2. The satellite based input forecast is based on our operational satellite forecast at DLR-VE and has a horizon of 6 hours with a step and update of 15 minutes. The satellite domain is reduced to the same 40 km2 area. The method consists on 3 blocks, forecasts homogenization, regression and prediction. In the homogenization block the satellite forecast is interpolated in space and time to the resolutions of the ASI network forecast. We applied linear interpolation for both resolutions as first test case. In the second block, a linear regression is applied to find the optimal weights of the linear combination of the forecast inputs, including a bias term. The regression is based on timeseries extracted from the historical forecasts (features) where the reference are taken from the historical timeseries of ground measurements (samples). Historical data is used in order to indirectly characterize the mean actual local weather conditions on the domain. It is important to note that the regression is performed independently for every lead time. In the third block, we use the optimized weights and biases along with the present (not historical) forecasts to produce the hybrid forecasts. The hybrid forecasts resolutions are the same as the ASI based forecast. The output product can be given as maps or timeseries. For the test case, we are limited from the ASI network side to a dataset of 2 full months of forecasts (July and August 2020). The highly resolved hybrid forecast was validated against the individual input sources and satellite persistence. We found that this newly developed forecast outperforms the RMSE of persistence and the individual input forecasts for all lead times calculated. It shows an improvement on RMSE of 5.07% to 13.97% with respect to satellite forecasts and 7.55% to 15.09% with respect to the ASI network forecast on lead times going from 5 to 30 minutes. It also shows a lower RMSE under high variability conditions

A network of all sky imagers (ASI) enabling accurate and high-resolution very short-term forecasts of solar irradiance

The Eye2Sky network is a measurement network in north-western Germany consisting of multiple all-sky imagers (ASI), meteorological and solar irradiance measurements. The network provides high temporal and spatial resolution data for meteorological and especially solar energy related applications. With increasing photovoltaic (PV) capacity in electrical grids fluctuations in solar irradiance due to changing cloud cover may have adverse effects on the grid stability. Within Eye2Sky, new technologies and methodologies facing the demand for more accurate solar irradiance forecasts are being developed. The ASIs used in Eye2Sky record 180° field of view hemispherical sky images from fish-eye lensed cameras. Accompanied with local measurements of solar irradiance components (global, direct and diffuse) a very short-term forecast of the solar resource is possible. These nowcasts provide minutely updated information up to 20 minutes ahead with 1-minute temporal and 50 m x 50 m spatial resolution. This approach shows more precise forecasting results for the next minutes ahead compared to traditional and less detailed methods based on satellite or numerical weather prediction models. In the network, multiple ASIs are used to enlarge the spatial coverage and the forecast horizon requested by many applications. Moreover, the forecast error can be reduced with a network of cameras. In this article, the Eye2Sky network, its research results and applications are introduced