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We observed the recently discovered FRB 20220912A (ATel #15679) with an ad-hoc VLBI network as part of the PRECISE project. We targeted the source on three occasions: 22 Oct UT 00:00-04:30, 24-25 Oct UT 21:00-02:00, and 26-27 Oct UT 23:00-04:30.

8th World Conference on Photovoltaic Energy Conversion; 1441-1445, The accumulation of dust on PV modules is one of the main causes of energy yield loss of PV power plants operated in desert climates. In this paper, we present analytical methods for assessing PV soiling impacts and a methodology for establishing a site-specific soiling metric. A generalized method for calculating the cost-optimized cleaning interval as a function of the average daily soiling rate is discussed. The experimental data for our study were obtained from a soiling station at KAUST University in Thuwal, Saudi Arabia. Soiling monitoring was performed with encapsulated c-Si reference cells (mini-module design) that were subjected to different cleaning intervals (daily, weekly and monthly). Our database included more than 3 years high-resolution data with a data recording interval of 30 seconds.

Hintergrund/Fragestellung/Problem: Die Versorgungsforschung ist in größeren Organisationen (Universtäten, Kliniken) meist dezentral aufgestellt. Dies spiegelt sich i. d. R. auch in einer zersplitterten Präsentation der laufenden Forschungsprojekte sowie der Angebote im [zum vollständigen Text gelangen Sie über die oben angegebene URL]

Hintergrund/Fragestellung/Problem: Geschlechtsidentität und sexuelle Orientierung sind wichtige Diversitätskategorien. In beiden Kategorien gibt es besonders vulnerable Gruppen in der medizinischen Versorgung. Standardmäßig wird in der Versorgungsforschung bisher Geschlecht [zum vollständigen Text gelangen Sie über die oben angegebene URL]

38th European Photovoltaic Solar Energy Conference and Exhibition; 550-555, The aim of this work was to re-evaluate the Climate Specific Energy Rating (CSER) methodology with regard to modelling the temperature of PV modules as defined in the IEC 61853 series of standards "Photovoltaic (PV) module performance testing and energy rating". The temperature behaviour of PV modules is described by a simple model in which the effects of light absorption and wind are considered by two modelling parameters u0 and u1. These are derived from a series of measurements under natural sunlight, from which only data points that meet certain stability criteria for solar irradiance and wind speed are used for linear regression (Method A). Our work addresses the shortcomings of the IEC data filter reported by test laboratories in the past: a) small number of filtered data points, b) filtered data points are not well distributed in the wind speed range. Both can lead to considerable uncertainty in the modelling parameters. We investigated an alternative data filter that provides a higher number of usable data points and improves the robustness of the regression by wind speed binning (Method 2). Furthermore, we introduce two indicators for the quality of the regression: a) the mean bias error with respect to the differences between measured and modelled temperatures and b) the irradiance-weighted module temperatures. Based on these indicators, a third method for determining u0 and u1 was investigated that does not require data filtering (Method 3) and focuses only on the best fit of modelled and measured module temperatures. For a measurement series from New Mexico with mostly clear skies, the application of the three methods resulted in a large scatter of the u0 and u1 parameters, but comparable NMOT values. Furthermore, the evaluation of a measurement series from Germany showed a scattering of the modelling parameters due to the measurement season mainly for Methods A and B. Our results confirm clear advantages for Method C. It is easy to apply, the data collection period can be kept short and the parameters u0 and u1 are less sensitive to seasonal variations.

37th European Photovoltaic Solar Energy Conference and Exhibition; 1120-1125, The aim of this work was to re-evaluate the correction procedure 2 detailed in the IEC 60891, ed.2, because deviat ions (within 0.5% in PMAX and 1.0% in VOC) in the region between the maximum power point and open-circuit voltage have been observed between experimental and t ranslated IV curves in PERC module types. The equat ions used in correction procedure 2 were revised to account for: 1. non-linear scaling of VOC against logarithmic irradiance, 2. irradiance-dependent temperature coefficient of voltage, 3. backward compat ibility of IV t ranslat ion and 4. temperature dependence of series resistance. The new modified set of equat ions showed a reduct ion in the observed deviat ions between t ranslated and measured I-V curves, when compared to the use of the original formulas. The improvements are noticeable in VOC, where accuracy gains up to 2.5% have been observed. Smaller in magnitude (up to 0.3%) but systemat ic accuracy gains were also observed in PMAX.

37th European Photovoltaic Solar Energy Conference and Exhibition; 811-815, The IEC 61853 standard series “Photovoltaic (PV) module performance testing and energy rating” aims to provide a standardized measure for PV module performance, namely the Climate Specific Energy Rating (CSER). An algorithm to calculate CSER is specified in part 3 based on laboratory measurements defined in parts 1 and 2 as well as the climate data set given in part 4. To test the comparability and clarity of the algorithm in part 3, we share the same input data, obtained by measuring a standard photovoltaic module, among different research organizations. Each participant then uses their individual implementations of the algorithm to calculate the resulting CSER values. The initial blind comparison reveals differences of 0.133 (14.7%) in CSER between the ten different implementations of the algorithm. Despite the differences in CSER, an analysis of intermediate results revealed differences of less than 1% at each step of the calculation chain among at least three participants. Thereby, we identify the extrapolation of the power table, the handling of the differences in the wavelength bands between measurement and climate data set, and several coding errors as the three biggest sources for the differences. After discussing the results and comparing different approaches, all participants rework their implementations individually and compare the results two more times. In the third intercomparison, the differences are less than 0.029 (3.2%) in CSER. When excluding the remaining three outliers, the largest absolute difference between the other seven participants is 0.0037 (0.38%). Based on our findings we identified four recommendations for improvement of the standard series.