The IEC 61853 standard series aims to provide a standardized measure for PV module energy rating, namely the Climate Specific Energy Rating (CSER). For this purpose, it defines procedures for the experimental determination of input data and algorithms for calculating the CSER. However, some steps leave room for interpretation regarding the specific implementation. To analyze the impact of these ambiguities, the comparability of results and the clarity of the algorithm for calculating the CSER in part 3 of the standard, an intercomparison is performed among research organizations with 10 different implementations of the algorithm. We share the same input data, obtained by measurement of a commercial crystalline silicon PV module, among the participating 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. After several comparison phases, a best practice approach is defined, which reduces the difference by a factor of 210 to below 0.001 (0.1%) in CSER for two independent PV modules. The best practice presented in this paper establishes clear guidelines for the numerical treatment of the spectral correction and power matrix extrapolation, where the methods in the standard are not clearly defined.Additionally, we provide input data and results for the PV community to test their implementations of the standard's algorithm. To identify the source of the deviations, we introduce a climate data diagnostic set. Based on our experiences, we give recommendations for the future development of the standard.

This contribution reports on a yearlong spectral albedo measurement campaign performed in Roskilde, Denmark. Four albedo scenarios are monitored using three sensor types. The ground surfaces include green grass, dry grass, gravel, and snow all of which have been monitored with albedometers based on spectroradiometers, silicon-pyranometers, and thermopile pyranometers. Implications of using the various albedo data sources/assumptions in bifacial PV modeling are assessed with the spectrally weighted bifacial energy gain (BEG). We find that BEG differs by as much as 3% with the different albedo sensors and BEG can deviate by as much as 7% from the ground truth when an incorrect static spectral albedo assumption is used. Finally, the spectral mismatch factor (SMM) is calculated to summarize rear plane of array (POA) spectral shifts. Our measurements show midday backside POA spectral shifts as high as 25% for Silicon bifacial PV devices mounted on single axis trackers above grass.