Publications

The purpose of this protocol is to bring metal halide perovskite (MHP) modules to a repeatable and relevant state prior to making a performance measurement. Performance measurements are made before and after a stressor has been applied to the module to quantify the degree of loss resulting from the stressor. This procedure is intended to be carried out both before and after the accelerated test.

The Perovskite PV Accelerator for Commercial Technology (PACT) is an independent validation center for the evaluation of perovskite PV technologies and their bankability. The center is led by Sandia National Laboratories and the National Renewable Energy Laboratory (NREL) and includes as part of its team Los Alamos National Laboratory (LANL), CFV Labs, Black and Veatch (B&V), and the Electric Power Research Institute (EPRI). The goals of the center are to: Develop and improve indoor and outdoor performance characterization methods, Develop and validate accelerated qualification testing for early failures (5-10 years), Research degradation and failure modes, Validate outdoor performance, and Provide bankability services to US perovskite PV (PSC) industry. The importance of data and data management to the success and outcomes of the PACT center is paramount. This report describes how data will be managed and protected by PACT and identifies important data management principles that will guide our approach.

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.

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Literature describes various methods for determining a series resistance for a photovoltaic device from measured IV curves. We investigate use of these techniques to estimate the series resistance parameter for a single diode equivalent circuit model. With simulated IV curves we demonstrate that the series resistance values obtained by these techniques differ systematically from the known series resistance parameter values used to generate the curves, indicating that these methods are not suitable for determining the series resistance parameter for the single diode model equation. We present an alternative method to determine the series resistance parameter jointly with the other parameters for the single diode model equation, and demonstrate the accuracy and reliability of this technique in the presence of measurement errors.

US Manufacturer Nishati provided three prototype, 72-cell photovoltaic modules to Sandia for characterization under the US Department of Energy Small Business Voucher program. Nishati is developing the Endurance^© product to address the stringent requirements associated with PV system installations sited near airports and military bases. These prototype modules are uniquely constructed of a polymeric matrix and an internal honeycomb structural element. Target features of the module design are reduced reflectivity from the front surface and reduced weight. Sandia applied a variety of in-house characterization methods to these modules with the goal of validating performance and identifying any areas for improvement. Reflectance testing revealed extremely low specular reflection, dramatically surpassing the performance of industry standard PV panels. Electrical performance testing validated performance in line with expectations for similar size and power class modules. Complimentary to reflection testing, outdoor angle of incidence testing indicated performance far exceeding expectations for industry standard PV panels. It is possible that the extremely low reflectance properties of these modules will convey an advantage in annual energy production in comparison to industry standard modules. Detailed performance modeling and experimental field validation would be required to verify this possible advantage. During the course of this testing, no obvious deficiencies in this module design were discovered. It is recommended that Nishati and Sandia proceed to the final Task associated with the SBV award. This final task will involve fielding modules at Sandia for reliability and energy production validation.

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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.

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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

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Monitoring of photovoltaic (PV) systems can maintain efficient operations. However, extensive monitoring of large quantities of data can be a cumbersome process. The present work introduces a simple, inexpensive, yet effective data monitoring strategy for detecting faults and determining lost revenues automatically. This was achieved through the deployment of Raspberry Pi (RPI) device at a PV system's combiner box. The RPI was programmed to collect PV data through Modbus communications, and store the data locally in a MySQL database. Then, using a Gaussian Process Regression algorithm the RPI device was able to accurately estimate string level current, voltage, and power values. The device could also detect system faults using a Support Vector Novelty Detection algorithm. Finally, the RPI was programmed to output the potential lost revenue caused by the abnormal condition. The system analytics information was then displayed on a user interface. The interface could be accessed by operations personal to direct maintenance activity so that critical issues can be solved quickly.

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.

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Commonly used performance models, such as PVsyst, Sandia Array Performance Model (SAPM), and PV LIB, treat the PV array as being constructed of identical modules. Each of the models attempts to account for mismatch losses by applying a simple percent reduction factor to the overall estimated power. The present work attempted to reduce uncertainty of mismatch losses by determining a representative set of performance coefficients for the SAPM that were developed from a characterization of a sample of modules. This approach was compared with current practice, where only a single module’s thermal and electrical properties are testing. However, the results indicate that minimal to no improvements in model predictions were achieved.

The texture or patterning of soil on PV surfaces may influence light capture at various angles of incidence (AOI). Accumulated soil can be considered a microshading element, which changes with respect to AOI. Laboratory deposition of simulated soil was used to prepare test coupons for simultaneous AOI and soiling loss experiments. A mixed solvent deposition technique was used to consistently deposit patterned test soils onto glass slides. Transmission decreased as soil loading and AOI increased. Dense aggregates significantly decreased transmission. However, highly dispersed particles are less prone to secondary scattering, improving overall light collection. In order to test AOI losses on relevant systems, uniform simulated soil coatings were applied to split reference cells to further examine this effect. The measured optical transmission and area coverage correlated closely to the observed ISC. Angular losses were significant at angles as low as 25°.

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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.

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Cost effective integration of solar photovoltaic (PV) systems requires increased reliability. This can be achieved with a robust fault detection and diagnostic (FDD) tool that automatically discovers faults. This paper introduces the Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network to perform this task. The present work tested the algorithm on actual and synthetic data to assess its potential for wide spread implementation. The tests were conducted on a PV system located in Albuquerque, New Mexico. The system was composed of 14 modules arranged in a configuration that produced a maximum power of 3.7kW. The LAPART algorithm learned system behavior quickly, and detected module level faults with minimal error.

The texture or patterning of soil on PV surfaces may influence light capture at various angles of incidence. Accumulated soil can be considered a micro-shading element, which changes with respect to AOI. While scattering losses at this scale would be significant only to the most sensitive devices, micro-shading could lead to hot spot formation and other reliability issues. Indoor soil deposition was used to prepare test coupons for simultaneous AOI and soiling loss experiments. A mixed solvent deposition technique was used to consistently deposit patterned test soils onto glass slides. Transmission decreased as soil loading and AOI increased. Highly dispersed particles are less prone to secondary scattering, improving overall light collection.

PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.

The Advanced Measurement and Analysis of PV Derate Factors project focuses on improving the accuracy and reducing the uncertainty of PV performance model predictions by addressing a common element of all PV performance models referred to as “derates”. Widespread use of “rules of thumb”, combined with significant uncertainty regarding appropriate values for these factors contribute to uncertainty in projected energy production.

The Characterizing Emerging Technologies project focuses on developing, improving and validating characterization methods for PV modules, inverters and embedded power electronics. Characterization methods and associated analysis techniques are at the heart of technology assessments and accurate component and system modeling. Outputs of the project include measurement and analysis procedures that industry can use to accurately model performance of PV system components, in order to better distinguish and understand the performance differences between competing products (module and inverters) and new component designs and technologies (e.g., new PV cell designs, inverter topologies, etc.).

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Soil accumulation on photovoltaic (PV) modules presents a challenge to long-term performance prediction and lifetime estimates due to the inherent difficulty in quantifying small changes over an extended period. Low mass loadings of soil are a common occurrence but remain difficult to quantify. In order to more accurately describe the specific effects of sparse soil films on PV systems, we have expanded upon an earlier technique to measure the optical losses due to an artificially applied obscurant film. A synthetic soil analog was sprayed onto glass coupons at very brief intervals with a high-volume, low-pressure pneumatic sprayer. Light transmission through the grime film was evaluated using a quantum efficiency test stand and UV/vis spectroscopy. A 0.1-g/m 2 grime loading was determined to be the limit of mass measurement sensitivity, which is similar to some reports of daily soil accumulation. Predictable, linear decreases in transmission were observed for samples with a mass loading between 0.1 and 0.5 g/m2. A similar change was observed for soiled coupons from an outdoor monitoring station. Collected soil from the field coupons was analyzed to develop a compositional analog for indoor studies. Natural and synthetic soils produced similar decreases in transmission.

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Soiling losses on high concentrating photovoltaic (HCPV) systems may be influenced by the spectral properties of accumulated soil. We have predicted the response of an isotype cell to changes in spectral content and reduction in transmission due to soiling using measured UV/vis transmittance through soil films. Artificial soil test blends deposited on glass coupons were used to supply the transmission data, which was then used to calculate the effect on model spectra. The wavelength transparency of the test soil was varied by incorporating red and yellow mineral pigments into graded sand. The more spectrally responsive (yellow) soils were predicted to alter the current balance between the top and middle subcells throughout a range of air masses corresponding to daily and seasonal variation.

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IEEE Standard 1547-2003 [1] conformance of several interconnected microinverters was performed by Sandia National Laboratories (SNL) to determine if there were emergent adverse behaviors of co-located aggregated distributed energy resources. Experiments demonstrated the certification tests could be expanded for multi- manufacturer microinverter interoperability. Evaluations determined the microinverters' response to abnormal conditions in voltage and frequency, interruption in grid service, and cumulative power quality. No issues were identified to be caused by the interconnection of multiple devices.

Soil accumulation on photovoltaic (PV) modules presents a challenge to long-term performance prediction and lifetime estimates due to the inherent difficulty in quantifying small changes over an extended period. Low mass loadings of soil are a common occurrence, but remain difficult to quantify. In order to more accurately describe the specific effects of sparse soil films on PV systems, we have expanded upon an earlier technique to measure the optical losses due to an artificially applied obscurant film. A synthetic soil analogue consisting of AZ road dust and soot in acetonitrile carrier solvent was sprayed onto glass coupons at very brief intervals with a high volume, low pressure pneumatic sprayer. Light transmission through the grime film was evaluated using a QE test stand and UV/vis spectroscopy. A 0.1 g/m2 grime loading was determined to be the limit of mass measurement sensitivity, which is similar to some reports of daily soil accumulation. Predictable, linear decreases in transmission were observed for samples with a mass loading between 0.1 and 0.5 g/m2. Reflectance measurements provided the best means of easily distinguishing this sample from a reference.

This manuscript is intended to serve as a practical guide to conducting repeatable indoor soiling experiments for PV applications. An outline of techniques, materials and equipment used in prior studies [1-3] is presented. Additional recommendations and practical guidance has been presented. Major sections include techniques to formulate soil simulants, ('standard grime') and feedstocks from traceable components, spray application, and quantitative measurement methodologies at heavy and minimal soil loadings.

The solar spectrum varies with atmospheric conditions and composition, and can have significant impacts on the output power performance of each junction in a concentrating solar photovoltaic (CPV) system, with direct implications on the junction that is current-limiting. The effect of changing solar spectrum on CPV module power production has previously been characterized by various spectral performance parameters such as air mass (AM) for both single and multi-junction module technologies. However, examinations of outdoor test results have shown substantial uncertainty contributions by many of these parameters, including air mass, for the determination of projected power and energy production. Using spectral data obtained from outdoor spectrometers, with a spectral range of 336nm-1715nm, this investigation examines precipitable water (PW), aerosol and dust variability effects on incident spectral irradiance. This work then assesses air mass and other spectral performance parameters, including a new atmospheric component spectral factor (ACSF), to investigate iso-cell, stacked multijunction and single-junction c-Si module performance data directly with measured spectrum. This will then be used with MODTRAN5® to determine if spectral composition can account for daily and seasonal variability of the short-circuit current density Jsc and the maximum output power Pmp values. For precipitable water, current results show good correspondence between the modeled atmospheric component spectral factor and measured data with an average rms error of 0.013, for all three iso-cells tested during clear days over a one week time period. Results also suggest average variations in ACSF factors with respect to increasing precipitable water of 8.2%/cmH2O, 1.3%/cmH2O, 0.2%/cmH2O and 1.8%/cmH2O for GaInP, GaAs, Ge and c-Si cells, respectively at solar noon and an AM value of 1.0. For ozone, the GaInP cell had the greatest sensitivity to increasing ozone levels with an ACSF variation of 0.07%/cmO3. For the desert dust wind study, consistent ACSF behavior between all iso-cells and c-Si was found, with only significant reductions beyond 40mph.

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