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

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

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

Comparison of short-term (hour-ahead) solar irradiance forecasts from all-sky imagers and satellite images

The all sky imagers (ASI) network Eye2Sky has been used for short-term solar irradiance forecasting in the urban area of the city of Oldenburg, in northwest Germany. Eye2Sky is a network of ASI and meteorological measurement instruments operated by DLR. This network is the basis for very short-term, high resolution and accurate predictions of solar irradiance in the upcoming minutes (nowcast). A high density of ASI with low spatial distances between cameras in the urban area allow an almost full coverage of the city (about 10x12 km). On the other hand, ASI-based solar irradiance nowcasts lack long forecast horizons due to their limited field of view (typically 15 minutes for single cameras). With a network of ASIs not only the coverage is increased but also the forecast horizon. Forecasting methods based on satellite images or numerical weather prediction (NWP) models are use as the standard for solar power forecasts. They provide larger spatial coverages and longer forecast horizons compared to ASI forecasts. On the contrary, due to their limited resolution and update rates the accuracy for short-term horizons and single sites is reduced. Here, we demonstrate the value of a network of ASI inside an urban environment for the spatial coverage and forecast horizon. Moreover, we show a comparison of forecast accuracy between the ASI nowcasts and the reference forecasts from satellite and a NWP model. These studies are the basis for a seamless forecasting strategy covering always finer spatial and temporal scales for intra-day applications. The main objective is to provide the highest available accuracy based on the hybridization of multiple data sources. We are looking for an intensive exchange with research and industry on the application of short-term solar forecasting in modern renewable energy driven energy systems, e.g. the use of short-term forecasts in the operation of large PV plants. Any feedback from stakeholders on their needs and requirements will support us to adapt nowcasting strategies to specific applications

Solar irradiance nowcasting based on a network of all sky imagers: the value of high-resolution data on variability information

The transition to a fossil-free energy system requires rapid installation of photovoltaic (PV) systems. For Germany, the government is targeting an installed PV capacity of 215 Gigawatt by 2030 (70 GW by 2023). This target is associated with an increased installation rate of 22 gigawatts PV per year (around three times compared to the 2021 rate). In urban areas, the majority of systems will be installed on rooftops connected to the low-voltage grid. It is therefore likely, that the majority of suitable rooftops will be equipped with PV systems in the next 10 years. In parallel, significant changes in load patterns (e.g. e-mobility, heat pumps) and the integration of battery storages can be expected. The efficient integration of the additional PV systems into the electrical grid also requires a detailed understanding of the generation profiles at different levels from the household to the transformer. Therefore, the impact of very-short-term solar irradiance variability on ramp rates and balancing effects should be investigated for scenarios with decentralized, but denser PV generation than today. Since this variability is mainly caused by small scale cloud dynamics, high resolution information on temporal and spatial cloud cover and irradiance distribution is needed. In northwestern Germany, DLR has installed and is operating Eye2Sky, a dense network of all-sky imagers (ASI). At 30 different locations, high-resolution fisheye images of the sky are taken every 30 seconds. At 10 locations, the images are complemented by radiation and meteorological measurements. The Eye2Sky network covers about 100 km x 100 km centered at the city of Oldenburg. It has a low ASI density in rural areas and a high density in city of Oldenburg, thus providing an almost complete coverage of the city. Eye2Sky is used to study solar irradiance variability in the city of Oldenburg at a high spatial (50 meters) and temporal (30 seconds) resolution. This enables simulations of single rooftop PV systems. Compared to state-of-the art radiation data sources like satellite images or numerical weather models (NWP), the camera information in Eye2Sky resolves cloud details that cause solar irradiance fluctuations on small scales down to household level. In this work, we would like to present a solar irradiance nowcasting validation from the ASI network in Oldenburg and its comparison with methods based on satellite (MSG) as well as NWP (ICON-D2) data. Emphasis will be made on the ability of the different methods to reproduce the spatio-temporal variability under different cloud condition

Solar irradiance nowcasting based on a network of all sky imagers: the value of high-resolution data on variability information

The transition to a fossil-free energy system requires rapid installation of photovoltaic (PV) systems. For Germany, the government is targeting an installed PV capacity of 215 Gigawatt by 2030 (70 GW by 2023). This target is associated with an increased installation rate of 22 gigawatts PV per year (around three times compared to the 2021 rate). In urban areas, the majority of systems will be installed on rooftops connected to the low-voltage grid. It is therefore likely, that the majority of suitable rooftops will be equipped with PV systems in the next 10 years. In parallel, significant changes in load patterns (e.g. e-mobility, heat pumps) and the integration of battery storages can be expected. The efficient integration of the additional PV systems into the electrical grid also requires a detailed understanding of the generation profiles at different levels from the household to the transformer. Therefore, the impact of very-short-term solar irradiance variability on ramp rates and balancing effects should be investigated for scenarios with decentralized, but denser PV generation than today. Since this variability is mainly caused by small scale cloud dynamics, high resolution information on temporal and spatial cloud cover and irradiance distribution is needed. In northwestern Germany, DLR has installed and is operating Eye2Sky, a dense network of all-sky imagers (ASI). At 30 different locations, high-resolution fisheye images of the sky are taken every 30 seconds. At 10 locations, the images are complemented by radiation and meteorological measurements. The Eye2Sky network covers about 100 km x 100 km centered at the city of Oldenburg. It has a low ASI density in rural areas and a high density in city of Oldenburg, thus providing an almost complete coverage of the city. Eye2Sky is used to study solar irradiance variability in the city of Oldenburg at a high spatial (50 meters) and temporal (30 seconds) resolution. This enables simulations of single rooftop PV systems. Compared to state-of-the art radiation data sources like satellite images or numerical weather models (NWP), the camera information in Eye2Sky resolves cloud details that cause solar irradiance fluctuations on small scales down to household level. In this work, we would like to present a solar irradiance nowcasting validation from the ASI network in Oldenburg and its comparison with methods based on satellite (MSG) as well as NWP (ICON-D2) data. Emphasis will be made on the ability of the different methods to reproduce the spatio-temporal variability under different cloud condition

Improving the satellite retrieval of surface solar irradiance during an eclipse

Solar eclipse causes high magnitude fluctuations in the Surface Solar Irradiance (SSI) for a short duration and consequently reduces the output of solar PV systems. Grid operators try to estimate the impending loss in PV power generation prior to the occurrence of an eclipse in order to schedule conventional generators for compensating the loss. The worldwide installed capacity of grid connected solar PV systems is expected to steeply rise in the coming decade as a result of the various policy initiatives aimed to tackle the climate change. In future electric supply networks with a high penetration of solar PV systems, such large ramps in generation could impact the stability of the network. Although a solar eclipse is a purely deterministic phenomenon, it’s impact on the satellite retrieval of Surface Solar Irradiance (SSI) is complicated due to the possibility of cloud presence in the regions affected by the eclipse. The extraterrestrial solar irradiance is reduced by the moon during an eclipse. On the one hand this causes clouds to appear darker and they get assigned lower reflectance values than they should have in reality. This leads to predicting higher values for the solar irradiance under these clouds than expected. On the other hand, the eclipse also reduces the clear sky irradiance reaching the earth surface. We developed a method to make corrections for both of these effects on the High Resolution Visible (HRV) channel images from Meteosat-11 The results are validated against ground measurements of irradiance provided by BSRN, IEA-PVPS, DTN and the National Weather Services networks. The validation is performed for sites with locations across Europe and for the last two eclipses

Observing Clouds from above and below - a chance for Redispatch 2.0?

Balancing the power production and energy demand is a constant activity of electricity grid operators. Since October 2021, distribution system operators (DSO) in Germany have a completely new role in redispatch as they have now to collaborate more actively with transmission grid operators (TSO) in their daily operations. Important new tasks of the DSO in the Redispatch 2.0 are now the use of daily feed-in forecasts, ensuring the network effectiveness and calculating flexibility restrictions on grid node levels. For these tasks they need to know the photovoltaic power feed in the next minutes and hours. DLR’s high resolution hybrid irradiance forecast is currently based on the combination of a Meteosat satellite derived forecast (based on the Heliosat 3 method) and forecasts derived from the All Sky Imager (ASI) network Eye2Sky. DLR’s Eye2Sky is a cloud monitoring system covering roughly 110x100 km in north-west Germany. It is equipped with 38 all sky imagers, i.e. sky-facing fisheye cameras, ten solar irradiance measurement stations and two individual instruments for cloud height measurement (Ceilometer) distributed throughout the region. The system collects high-resolution information on solar irradiance , tracks the variability and provides forecasts for very short time scales. It has a spatial resolution 50 meters and the temporal resolution exceeds 1 minute. It can produce forecasts for up to one hour ahead depending on the prevailing cloud height and velocity. The data can inform about present and future weather (solar irradiance) conditions for the reliable operation of distribution grids, and economic operation of solar installations as well as for regional case studies. Outcomes of the Smart4RES project show that the hybrid forecast outperforms the RMSE of persistence and the individual input forecasts for all lead times (5min to 30min) for a first validation period of two months (July and August 2020). So, it is a promising candidate for assisting DSOs in their new tasks in Redispatch 2.0. Coupling cloud observations from above (satellite) and below (ground observations) combines the pros and cons of each observing system. We further analyze the cloud situation dependent accuracy of the forecast methods and assess the impact of the assumptions in satellite retrievals on their performances

Evaluation of ECMWF HRES IFS and CAMS IFS intra- and day-ahead forecasts with respect to surface solar irradiances

The main focus of the CAMS Radiation Service is to provide high-quality long-term historical irradiance data which is easily integrated in solar resource assessments and other related studies. At the same time, the CAMS system provides a forecast of atmospheric conditions, that is, aerosols, water vapor and ozone. As part of its Integrated Forecasting System (IFS), ECMWF generates an alternative forecast which uses additional modules based on the atmospheric conditions forecasted by CAMS, which we name the CAMS IFS forecast (Inness et al., 2015). It is an overarching question, whether the CAMS IFS forecast provides radiation forecasts in a similar or better quality as the operational HRES IFS forecast and whether it could be implemented as an operational product on itself. The IFS CAMS forecast is operated on a low spatial resolution of 40 km (~ 3.5°). This is coarse compared to the 9 km (~0.1°) spatial resolution of the operational HRES IFS, but the CAMS IFS runs are based on additional aerosol forecasts provided by CAMS while the operational ECMWF IFS runs use an aerosol climatology (Bozzo et al., 2017). The present evaluation is done for the full year 2021 on a global scale using ground observations from well-known research quality solar radiation measurement networks (BSRN, SOLRAD, SURFRAD, enerMENA, NREL-MIDC). Following solar energy stakeholders needs, this evaluation will be concentrated on the intraday and day-ahead range, that is, the evaluation will use the forecasts up to 48 hours. The forecasts are obtained from the run at 0 UTC which ensures that the forecasts are available for all intraday and day ahead market transactions and operational processes. Both forecasts sources have a native time resolution of 1 hour in their public accessible output, therefore, the evaluation is also performed on an hourly resolution basis