Photovoltaic modules are subjected to various mechanical stressors in their deployment environments, ranging from installation handling to wind and snow loads. Damage incurred during these mechanical events has the potential to initiate subsequent degradation mechanisms, reducing useful module lifespan. Thus, characterizing the mechanical state of photovoltaic modules is pertinent to the development of reliable packaging designs. In this work, photovoltaic modules with strain gauges directly incorporated into the module laminate were fabricated and subjected to mechanical loading to characterize internal strains within the module when under load. These experimental measurements were then compared against results obtained by high-fidelity finite-element simulations. The simulation results showed reasonable agreement in the strain values over time; however, there were large discrepancies in the magnitudes of these strains. Both the instrumentation technique and the finite-element simulations have areas where they can improve. These areas of improvement have been documented. Despite the observed discrepancies between the experimental and simulated results, the module instrumentation proved to be a useful gauge in monitoring and characterizing the mechanical state. With some process improvements, this method could potentially be applied to other environments that a photovoltaic module will encounter in its lifetime that are known to cause damage and degrade performance.
Studying the mechanical behavior of silicon cell fractures is critical for understanding changes in PV module performance. Traditional methods of detecting cell cracks, e.g., electroluminescence (EL) imaging, utilize electrical changes and defects associated with cell fracture. Therefore, these methods reveal crack locations, but do not operate at the time or length scales required to accurately measure other physical properties of cracks, such as separation width and behavior under dynamic loads.
Using a photovoltaic module where each of the 72 cells are monitored separately, we have measured the optical effects of sunlight hitting the module at different angles. As the angle of incidence increased to 60-70 degrees, we observed an increase in the nonuniformity of the light reaching the cells across the module area (up to 4% as measured by resulting cell current). The effect is hypothesized to be the result of a combination of two mechanisms: light trapping within the top sheet glass layer and reflection from the aluminum frame at the edge of the module. We confirm these effects with time-series measurements on split reference cells fielded outdoors, and with ray-tracing modeling to determine how this phenomenon may affect PV performance and module characterization.
Photovoltaic (PV) module and system performance degradation is being measured by periodic flash testing of fielded PV modules at three sites. As of early 2018, results from modules fielded in New Mexico and Colorado are now available. These data indicate that module degradation varies significantly between module types and can also vary between modules of the same model. In addition, degradation rates for some module types appear to vary over time. Great care is made to control for stability and repeatability in the measurements over time, but there is still a +/-0.5% uncertainty in flash test stability. Therefore, it will take several more years for degradation rate results to be known with higher confidence.
Copper indium gallium (di)serenade (CIGS) photovoltaic cell technology has long been promoted as a cost-effective alternative to traditional PV modules based on crystalline silicon cells. However, adoption of CIGS is hindered by significant uncertainties regarding long-term reliability and performance stability, as well as a lack of accurate modeling tools to predict CIGS system performance. Sandia is conducting a multi-year study of fielded CIGS systems that range in age from 3-6 years and represent a cross-section of commercial manufacturing and packaging. Most of these arrays include modules that were thoroughly characterized prior to deployment. In this paper, we explore uncertainty in the long-term reliability and performance stability of CIGS modules by analyzing real world performance and degradation rates of these systems.
Angle of incidence response of a photovoltaic module describes its light gathering capability when incident sunlight is at an orientation other than normal to the module's surface. At low incident angles (i.e. close to normal), most modules have similar responses. However, at increasing incident angles, reflective losses dominate response and relative module performance becomes differentiated. Relative performance in this range is important for understanding the potential power output of utility - scale ph otovoltaic systems. In this report, we document the relative angle of incidence response of four utility - grade panels to each other and to four First Solar modules. We found that response was nearly identical between all modules up to an incident angle of ~55°. At higher angles, differences of up to 5% were observed. A module from Yingli was the best performing commercial module while a First Solar test module with a non - production anti - reflective coating was the best overall performer. This page left blank
Current-voltage (I-V) curve traces of photovoltaic (PV) systems can provide detailed information for diagnosing fault conditions. The present work implemented an in situ, automatic I-V curve tracer system coupled with Support Vector Machine and a Gaussian Process algorithms to classify and estimate abnormal and normal PV performance. The approach successfully identified normal and fault conditions. In addition, the Gaussian Process regression algorithm was used to estimate ideal I-V curves based on a given irradiance and temperature condition. The estimation results were then used to calculate the lost power due to the fault condition.
The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.
The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented comparisons of measurements and analysis results among laboratories, detailed procedures for determining model coefficients have not yet been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. Here we present a standard procedure for calibrating the SAPM using outdoor electrical and meteorological measurements. Analysis procedures are illustrated with data measured outdoors for a 36-cell silicon photovoltaic module.
We present a method for measuring the series resistance of the PV module, string, or array that does not require measuring a full IV curve or meteorological data. Our method relies only on measurements of open circuit voltage and maximum power voltage and current, which can be readily obtained using standard PV monitoring equipment; measured short circuit current is not required. We validate the technique by adding fixed resistors to a PV circuit and demonstrating that the method can predict the added resistance. Relative prediction accuracy appears highest for smaller changes in resistance, with a systematic underestimation at larger resistances. Series resistance is shown to vary with irradiance levels with random errors below 1.5% standard deviation.