• Energy Research

This paper analyzes 15-months of spectral albedo measurements collected at the Technical University of Denmark (55.6°N, 12.1°E). High-resolution spectroradiometers are used to monitor four albedo scenarios, which include green vegetation, dry vegetation, gravel, and snow. Spectral mismatch and spectral impact are calculated for the front and backside of three different bifacial cell concepts mounted on horizontal single axis trackers and fixed-tilt substructures. The spectral nature of albedo is shown to have significant influence on bifacial photovoltaic performance wherein backside spectral impact as high as 1.20 is observed for fixed-tilt systems above green vegetation and as low as 0.98 for systems above snow. The results reveal that spectral impact is always lower on tracked than fixed-tilt systems because a greater fraction of sky diffuse light reaches the backside of tracked systems. Given the variety of albedos tested here, we find that the normalized difference vegetation index is a good predictor of backside spectral effects. When the high-resolution measurements are truncated to 4 to 8 carefully selected wavelengths, we find that this limited measurement resolution sufficiently captures the seasonal spectral albedo fluctuations that influence bifacial photovoltaic energy production. Finally, to alleviate the dearth of spectral datasets presently available to the PV community, the spectral irradiance and albedo measurements are made freely available in open access format.

The heterogenous nature and spectral distribution of rear plane-of-array irradiance RPOA presents challenges when measured by small-area sensors such as pyranometers. Bifacial reference modules serving as large-area sensors can simplify irradiance monitoring because their electrical response follows that of the power generating modules in an array. This article compares RPOA and effective irradiance GE measured by calibrated reference modules against three commonly used small-area sensors including pyranometers, reference cells, and photodiodes. A technology-matched monofacial module is mounted side-by-side with the bifacial reference to decouple effective irradiance measurements into front and backside contributions. The results show that RPOA and GE measurements made with reference panels have the best correlation to reference cells. The mean absolute errors between the two measurement approaches are 9% relative, 4 W/m2 absolute for RPOA and 4% relative, 7 W/m2 absolute for GE. When GE measurements from the four sensor types are used to predict string-level power, the reference panel measurements show a 3.4% prediction error, which is comparable to that achieved when using GE measurements from pyranometers (3.0%) and reference cells (2.9%) thereby suggesting that reference modules can be used to accurately measure RPOA and GE in bifacial systems.

An accurate energy yield estimation for building-integrated photovoltaic (PV) applications with colored glass under field conditions is a key factor for architects, building planners, and potential investors. The power output of these installations depends not only on the angle of incidence but also on the incident solar spectrum. The aim of this work is to simulate the short-circuit current of PV single-cell laminates with colored solar glass under field conditions. Therefore, we use angular-dependent spectral responsivity measurement data from a physical setup. Test samples with gold-, blue-, blue-green-, and gray-colored solar glass and a reference with standard solar glass, oriented on a tilted surface, are simulated. The results for one month of field validation indicate a good agreement with a relative root mean square error between 1.9% and 2.5% for the test samples. A model comparison reveals larger errors for the blue, blue-green, and gold test samples when the spectral responsivity at normal incidence and the incident angle modifier for broadband direct irradiation are used instead. It is concluded that short-circuit current simulation using indoor characterization from spectrally resolved measurement setups provides improved accuracy that is particularly suitable for bankable energy yield estimates of colored building-integrated PV modules.

This workbook includes all necessary data to run the bifacial PV simulations performed in:"Validation of Bifacial Photovoltaic Simulation Software Against Monitoring Data from Large-Scale Single-Axis Trackers and Fixed Tilt Systems in Denmark"Appl. Sci. 2020, 10(23), 8487; https://doi.org/10.3390/app10238487The workbook tabs include:-Site Data-Shade Scene-Structural Dimensions-PV Module Specifications-Inverter Specifications-Albedo Data-Meteorological Data-Validation (monitoring) Data If you use this data in a published work, please cite the publication and the dataset.

<p>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.</p>

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. 37th European Photovoltaic Solar Energy Conference and Exhibition; 811-815

Electroluminescence (EL) imaging is a photovoltaic (PV) module characterization technique, which provides high accuracy in detecting defects and faults, such as cracks, broken cells interconnections, shunts, among many others; furthermore, the EL technique is used extensively due to a high level of detail and direct relationship to injected carrier density. However, this technique is commonly practiced only indoors - or outdoors from dusk to dawn - because the crystalline silicon luminescence signal is several orders of magnitude lower than sunlight. This limits the potential of such a powerful technique to be used in utility scale inspections, and therefore, the interest in the development of electrical biasing tools to make outdoor EL imaging truly fast and efficient. With the focus of quickly acquiring EL images in daylight, we present in this article a drone-based system capable of acquiring EL images at a frame rate of 120 frames per second. In a single second during high irradiance conditions, this system can capture enough EL and background image pairs to create an EL PV module image that has sufficient diagnostic information to identify faults associated with power loss. The final EL images shown in this work reached representative quality SNR AVG of 4.6, obtained with algorithms developed in previous works. These drone-based EL images were acquired with global horizontal solar irradiance close to one sun in the plane of the array.