A unique non-destructive characterization method for apparent bandgap imaging in photovoltaic (PV) devices based on acquisition of two electroluminescence (EL) images in different spectral ranges is presented. The method consists of a calibration procedure and a bandgap imaging procedure. Calibration has to be performed once per module type and EL imaging setup, and must provide a relation between the bandgap and the ratio between two spectrally independent EL images. After calibration, bandgap imaging only requires acquisition of two spectrally independent EL images followed by image processing, making the method very fast and suitable for in-line PV module characterization with regard to spatial (in)homogeneity and production process stability. The method is demonstrated on a commercial state-of-the-art Cu(In,Ga) Se2 PV module where apparent bandgap fluctuations between 1.07 and 1.15 eV are detected.
COBISS.SI-ID: 11923028
A new in-situ moisture monitoring technique for photovoltaic (PV) modules is proposed using miniature digital humidity and temperature sensors. The sensors were embedded in three different ethylene-vinyl-acetate (EVA) stacks and proved to be resistant to lamination conditions. The fact that they are in direct contact to EVA does not affect their performance, since their saturated relative humidity (RH) reading is proportional to the external RH in the air. By exposing the sensors to elevated temperature and RH conditions, water vapor transmission rate of the backsheet and diffusion coefficient of the EVA can be determined. Obtained coefficients agree with reference values within their measurement uncertainties. Besides determining material moisture ingress properties, this monitoring technique is also applicable for long-term outdoor PV module monitoring. It shall provide valuable location and installation specific information of RH and temperature stress conditions, especially as feedback information to manufacturers of materials and PV modules.
COBISS.SI-ID: 11601748
To achieve higher accuracy in power rating of photovoltaic modules and systems we recently developed an advanced PV performance model that separately addresses the contribution of diffuse and direct solar irradiance. To further improve the accuracy, we upgraded the model in this study to include the influence of solar spectrum on PV module conversion efficiency. We measured solar spectrum in Ljubljana separately for diffuse and direct irradiances under different weather conditions and calculated spectral losses or gains compared to AM1.5 reference spectrum. For diffuse irradiance under clear sky conditions we detected spectral losses from 4.5% during morning hours and up to 23.9% at around noon. During cloudy conditions the average losses were 3.5% and the variation of losses during the day was hardly noticeable. For direct irradiance we detected spectral gains, ranging from 0.8% to 10.3% for air mass values from 1.1 to 5.0, respectively. We modeled obtained results of spectral influence on PV module performance by introducing spectral correction factor separately for direct irradiance with air mass as an input parameter and for diffuse irradiance with the share of diffuse irradiance as an input parameter. The spectral correction factors are applied to measured diffuse and direct irradiance which are then used as an input parameters of the developed PV performance model. We evaluated the increase of accuracy of the model with the spectral upgrade for one month and one year measurements of a silicon PV module at an outdoor monitoring test site in Ljubljana, Slovenia. For the month of June 2014 the normalized root-mean-square error of the spectrally upgraded model was 2.3% compared to 2.7% without spectral correction. For the eight snowless months period in 2014 the error of evaluated performance model improved from 3.7% to 3.3% when the spectral correction was applied.
COBISS.SI-ID: 11729748