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Transport accounts for 31% of Swiss green house gas emissions due to the high degree of oil dependence in transport energy supply. The emissions of transport could be reduced significantly if all the vehicles that ran on fossil fuels would be replaced by electric vehicles powered by photovoltaic solar energy. Compared with other sources of renewable transport energy, photovoltaic generation of electricity has two advantages: it requires little space and can also be applied to built-up areas or transport infrastructure. In this paper, we will examine the potential of parking lots for the photovoltaic generation of solar electricity. The paper is based on simulations that were carried out for 48 parking lots in Frauenfeld, a typical Swiss medium-sized city of 22 665 inhabitants. Covered with solar carports, these parking lots alone would cover 15-40% of the energy demand by the city's road passenger transport.

The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.

Hall-effect and photoluminescence measurements have been carried out on Sn-doped CuGaSe2 single crystals. The doping was performed either during chemical vapor transport growth with iodine or by a diffusion step at temperatures between 200 and 400 °C. Room temperature resistivity can be varied in the range between 10−2 and 106 Ω cm. Hall-effect data can be explained using a model containing two acceptor levels, one of which is very shallow, and a donor level. Due to doping the concentration of the first acceptor, whose activation energy is 59 meV, is decreased and the donor concentration is increased, but no n-type conductivity was observed. The photoluminescence spectra can be explained by an acceptor level of 50 meV, two donor levels of 80 and 110 meV, respectively, and a deep state of 400 meV. VCu, VSe, VSe complexes, and Sn on cation lattice sites are suggested as origins of these states.

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