Estimating PV Module Performance over Large Geographical Regions: The Role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum

We present a study of how photovoltaic (PV) module performance varies on continental scale. Mathematical models have been used to take into account shallow-angle reflectivity, spectral sensitivity, dependence of module efficiency on irradiance and module temperature as well as how the module temperature depends on irradiance, ambient temperature and wind speed. Spectrally resolved irradiance data retrieved from satellite images are combined with temperature and wind speed data from global computational weather forecast data to produce maps of PV performance for Eurasia and Africa. Results show that module reflectivity causes a fairly small drop of 2-4\% in PV performance. Spectral effects may modify the performance by up to +/- 6%, depending on location and module type. The strongest effect is seen in the dependence on irradiance and module temperature, which may range from -20% to +5% at different locations.JRC.F.7-Renewables and Energy Efficienc

A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation

We present a new database of solar radiation at ground level for Eastern Europe and Africa, the Middle East and Asia, estimated using satellite images from the Meteosat East geostationary satellites. The method presented calculates global horizontal (G) and direct normal irradiance (DNI) at hourly intervals, using the full Meteosat archive from 1998 to present. Validation of the estimated global horizontal and direct normal irradiance values has been performed by comparison with high-quality ground station measurements. Due to the low number of ground measurements in the viewing area of the Meteosat Eastern satellites, the validation of the calculation method has been extended by a comparison of the estimated values derived from the same class of satellites but positioned at 0ºE, where more ground stations are available. Results show a low overall mean bias deviation (MBD) of +1.63W/m-2 or +0.73\% for global horizontal irradiance. The mean absolute bias of the individual station MBD is 2.36\%, while the root mean square deviation of the individual MBD values is 3.18\%. For direct normal irradiance the corresponding values are overall MBD of +0.62W/m-2 or +0.62\%, while the mean absolute bias of the individual station MBD is 5.03\% and the root mean square deviation of the individual MBD values is 6.24\%. The resulting database of hourly solar radiation values will be made freely available. These data will also be integrated into the PVGIS web application to allow users to estimate the energy output of photovoltaic (PV) systems not only in Europe and Africa, but now also in Asia.JRC.F.7-Renewables and Energy Efficienc

Application of Satellite-Based Spectrally-Resolved Solar Radiation Data to PV Performance Studies

In recent years, satellite-based solar radiation data resolved in spectral bands have become available. This has for the first time made it possible to produce maps of the geographical variation in the solar spectrum. It also makes it possible to estimate the influence of these variations on the performance of photovoltaic (PV) modules. Here, we present a study showing the magnitude of the spectral influence on PV performance over Europe and Africa. The method has been validated using measurements of a CdTe module in Ispra, Italy, showing that the method predicts the spectral influence to within ±2% on a monthly basis and 0.1% over a 19-month period. Application of the method to measured spectral responses of crystalline silicon, CdTe and single-junction amorphous silicon (a-Si) modules shows that the spectral effect is smallest over desert areas for all module types, higher in temperate Europe and highest in tropical Africa, where CdTe modules would be expected to yield +6% and single- junction a-Si modules up to +10% more energy due to spectral effects. In contrast, the effect for crystalline silicon modules is less than ±1% in nearly all of Africa and Southern Europe, rising to +1% or +2% in Northern Europe.JRC.F.7-Renewables and Energy Efficienc

Comparison of satellite-retrieved high-resolution solar radiation datasets for South Africa

This study compares the performance of two satellite-based solar radiation methodologies for estimating the solar resource available in South Africa. Data from thirteen stations distributed in six climatic regions were considered. More than one year of hourly values of global horizontal and beam normal irradiance were examined in the validation of the satellite-retrieved estimates at every location. The best satellite method resulted in an overall relative mean bias of 1.41% for the global horizontal irradiance corresponding to almost 3 Wm-2 and exhibited a relative mean bias of 2.85% for the beam normal irradiance estimation (about 7 Wm-2). This satellite-based method was implemented into a geographical information system module, which contained high-resolution terrain data and allowed the effect of the surrounding topography on the estimation of the available solar resource to be considered. These estimates can, therefore, be used as input data for further analysis or applications. As an example, maps of the potential output that could be expected in South Africa from photovoltaic systems were created

Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data

This study examines the progress made by two new reanalyses in the estimation of surface irradiance: ERAS, the new global reanalysis from the ECMWF, and COSMO-REA6, the regional reanalysis from the DWD for Europe. Daily global horizontal irradiance data were evaluated with 41 BSRN stations worldwide, 294 stations in Europe, and two satellite-derived products (NSRDB and SARAH). ERAS achieves a moderate positive bias worldwide and in Europe of + 4.05 W/m 2 and + 4.54 W/m 2 respectively, which entails a reduction in the average bias ranging from 50% to 75% compared to ERA-Interim and MERRA-2. This makes ERAS comparable with satellite-derived products in terms of the mean bias in most inland stations, but ERAS results degrade in coastal areas and mountains. The bias of ERAS varies with the cloudiness, overestimating under cloudy conditions and slightly underestimating under clear-skies, which suggests a poor prediction of cloud patterns and leads to larger absolute errors than that of satellite-based products. In Europe, the regional COSMO-REA6 underestimates in most stations (MBE = -5.29 W/m(2)) showing the largest deviations under clear-sky conditions, which is most likely caused by the aerosol climatology used. Above 45 degrees N the magnitude of the bias and absolute error of COSMO-REA6 are similar to ERAS while it outperforms ERA5 in the coastal areas due to its high-resolution grid (6.2 km). We conclude that ERAS and COSMO-REA6 have reduced the gap between reanalysis and satellite-based data, but further development is required in the prediction of clouds while the spatial grid of ERAS (31 km) remains inadequate for places with high variability of surface irradiance (coasts and mountains). Satellite-based data should be still used when available, but having in mind their limitations, ERAS is a valid alternative for situations in which satellite-based data are missing (polar regions and gaps in times series) while COSMO-REA6 complements ERA5 in Central and Northern Europe mitigating the limitations of ERA5 in coastal areas.Peer reviewe

Photovoltaic energy systems

This report outlines the European Commission's Joint Research Centre's contribution to standardisation activities within the field of Photovoltaic Energy Systems. The Joint Research Centre (JRC) continues to play a significant role in European and international standardisation activities within the field of Photovoltaic Energy Systems. In particular JRC experts are convenors for working groups in both the relevant IEC and CENELEC technical committees, were the project leader of one standards published by the IEC in 2019 and made a significant contribution to many others. JRC is also the project leader for two more standards which are currently subject to the standardisation process.JRC.C.2-Energy Efficiency and Renewable

Transitional methods for PV modules, inverters and systems in an Ecodesign Framework

This document contains proposal for the establishment of transition methods in order to facilitate the introduction of regulations governing ECODESIGN , ECOLabel , Energy Label and GPP. This draft has been prepared for the 2nd Stakeholder Meeting for the PV Ecodesign Preliminary Study. The final version will be available at the conclusion of the preparatory study in 2019.JRC.C.2-Energy Efficiency and Renewable

Standards for the assessment of the environmental performance of photovoltaic modules, power conversion equipment and photovoltaic systems

To support the on-going preparatory activities on the feasibility of applying the EcoDesign, EU Energy label, EU Ecolabel and Green Public Procurement (GPP) policy instruments to solar photovoltaic modules, inverters and systems, this report aims to: • Identify, describe and compare existing standards and new standards under development, relevant to energy performance, reliability, degradation and lifetime. • Identify aspects not covered by existing standards, for which transitional methods may be needed.JRC.C.2-Energy Efficiency and Renewable

Quality control of global solar radiation data with satellite-based products

Several quality control (QC) procedures are available to detect errors in ground records of solar radiation, mainly range tests, model comparison and graphical analysis, but most of them are ineffective in detecting common problems that generate errors within the physical and statistical acceptance ranges. Herein, we present a novel QC method to detect small deviations from the real irradiance profile. The proposed method compares ground records with estimates from three independent radiation products, mainly satellite-based datasets, and flags periods of consecutive days where the daily deviation of the three products differs from the historical values for that time of the year and region. The confidence intervals of historical values are obtained using robust statistics and errors are subsequently detected with a window function that goes along the whole time series. The method is supplemented with a graphical analysis tool to ease the detection of false alarms. The proposed QC was validated in a dataset of 313 ground stations. Faulty records were detected in 31 stations, even though the dataset had passed the Baseline Surface Radiation Network (BSRN) range tests. The graphical analysis tool facilitated the identification of the most likely causes of these errors, which were classified into operational errors (snow over the sensor, soiling, shading, time shifts, large errors) and equipment errors (miscalibration and sensor replacements), and it also eased the detection of false alarms (16 stations). These results prove that our QC method can overcome the limitations of existing QC tests by detecting common errors that create small deviations in the records and by providing a graphical analysis tool that facilitates and accelerates the inspection of flagged values.Peer reviewe

Extensive validation of CM SAF surface radiation products over Europe

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8–13 W/m 2 , whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements