All freely available plane-of-array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib-python and pvpltools-python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853-1 and 61853-2 testing, and the input data for each model were sourced from these system-specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system-specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system-specific data.
Aging of silicon photovoltaic (PV) module packaging is one of the greatest limiters of PV module service lifetimes. Module characterization typically focuses on power degradation metrics, which do not convey the complexities of often simultaneous degradation mechanisms. In this work, PV modules with pristine references and known fielding histories were investigated by non-destructive and destructive methods. Modules from Canadian Solar, Mission Solar, and Hanwha Q-Cells were fielded for up to three years; select modules were removed from fielding each year for coring to allow for characterization of the encapsulant. Modules are commonly encapsulated with two protective layers of partially-crystalline ethylene vinyl acetate (EVA) polymer that must undergo a crosslinking reaction to achieve desired properties. The extent of crystallinity of the encapsulants as studied by differential scanning calorimetry showed differences between manufacturers and over time. Some encapsulants showed different magnitudes of crystal sizes which changed after fielding; encapsulants with the monodisperse crystal sizes did not change with fielding. This is due to differences in thermal history. These results have implications for stress development during module aging, since EVA crystal melting and crosslinking reactions can result in encapsulant density changes.
The purpose of this protocol is to define procedures and practices to be used by the PACT center for field testing of metal halide perovskite (MHP) photovoltaic (PV) modules. The protocol defines the physical, electrical, and analytical configuration of the tests and applies equally to mounting systems at a fixed orientation or sun tracking systems. While standards exist for outdoor testing of conventional PV modules, these do not anticipate the unique electrical behavior of perovskite cells. Further, the existing standards are oriented toward mature, relatively stable products with lifetimes that can be measured on the scale of years to decades. The state of the art for MHP modules is still immature with considerable sample to sample variation among nominally identical modules. Version 0.0 of this protocol does not define a minimum test duration, although the intent is for modules to be fielded for periods ranging for weeks to months. This protocol draws from relevant parts of existing standards, and where necessary includes modifications specific to the behavior of perovskites.
The cost of photovoltaic (PV) modules has declined by 85% since 2010. To achieve this reduction, manufacturers altered module designs and bill of materials; changes that could affect module durability and reliability. To determine if these changes have affected module durability, we measured the performance degradation of 834 fielded PV modules representing 13 module types from 7 manufacturers in 3 climates over 5 years. Degradation rates (Rd) are highly nonlinear over time, and seasonal variations are present in some module types. Mean and median degradation rate values of −0.62%/year and −0.58%/year, respectively, are consistent with rates measured for older modules. Of the 23 systems studied, 6 have degradation rates that will exceed the warranty limits in the future, whereas 13 systems demonstrate the potential of achieving lifetimes beyond 30 years, assuming Rd trends have stabilized.
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.
We evaluate the use of reference modules for monitoring effective irradiance in PV power plants, as compared with traditional plane-of-array (POA) irradiance sensors, for PV monitoring and capacity tests. Common POA sensors such as pyranometers and reference cells are unable to capture module-level irradiance nonuniformity and require several correction factors to accurately represent the conditions for fielded modules. These problems are compounded for bifacial systems, where the power loss due to rear side shading and rear-side plane-of-array (RPOA) irradiance gradients are greater and more difficult to quantify. The resulting inaccuracy can have costly real-world consequences, particularly when the data are used to perform power ratings and capacity tests. Here we analyze data from a bifacial single-axis tracking PV power plant, (175.6 MWdc) using 5 meteorological (MET) stations, located on corresponding inverter blocks with capacities over 4 MWdc. Each MET station consists of bifacial reference modules as well pyranometers mounted in traditional POA and RPOA installations across the PV power plant. Short circuit current measurements of the reference modules are converted to effective irradiance with temperature correction and scaling based on flash test or nameplate short circuit values. Our work shows that bifacial effective irradiance measured by pyranometers averages 3.6% higher than the effective irradiance measured by bifacial reference modules, even when accounting for spectral, angle of incidence, and irradiance nonuniformity. We also performed capacity tests using effective irradiance measured by pyranometers and reference modules for each of the 5 bifacial single-axis tracking inverter blocks mentioned above. These capacity tests evaluated bifacial plant performance at ∼3.9% lower when using bifacial effective irradiance from pyranometers as compared to the same calculation performed with reference modules.
We evaluate the use of reference modules for monitoring effective irradiance in PV power plants, as compared with traditional plane-of-array (POA) irradiance sensors, for PV monitoring and capacity tests. Common POA sensors such as pyranometers and reference cells are unable to capture module-level irradiance nonuniformity and require several correction factors to accurately represent the conditions for fielded modules. These problems are compounded for bifacial systems, where the power loss due to rear side shading and rear-side plane-of-array (RPOA) irradiance gradients are greater and more difficult to quantify. The resulting inaccuracy can have costly real-world consequences, particularly when the data are used to perform power ratings and capacity tests. Here we analyze data from a bifacial single-axis tracking PV power plant, (175.6 MWdc) using 5 meteorological (MET) stations, located on corresponding inverter blocks with capacities over 4 MWdc. Each MET station consists of bifacial reference modules as well pyranometers mounted in traditional POA and RPOA installations across the PV power plant. Short circuit current measurements of the reference modules are converted to effective irradiance with temperature correction and scaling based on flash test or nameplate short circuit values. Our work shows that bifacial effective irradiance measured by pyranometers averages 3.6% higher than the effective irradiance measured by bifacial reference modules, even when accounting for spectral, angle of incidence, and irradiance nonuniformity. We also performed capacity tests using effective irradiance measured by pyranometers and reference modules for each of the 5 bifacial single-axis tracking inverter blocks mentioned above. These capacity tests evaluated bifacial plant performance at ∼3.9% lower when using bifacial effective irradiance from pyranometers as compared to the same calculation performed with reference modules.
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.
Photovoltaic energy prediction models include functions or modifiers to account for sun angle reflection losses. These functions may be known interchangeably as Angle of Incidence (AOI) or Incident Angle Modifier (IAM). While standards exist, there is no universally accepted single best practice for developing these functions. They can be generated through characterization of representative modules or single cells, in natural sunlight or indoors using simulated light sources. Repeatability of measurements and the viability of cross-laboratory comparisons are critical to confidence in validation of both methods. To investigate the differences between methods and labs, The Technical University of Denmark (DTU) initiated an international round-robin test comparison between several key test labs with AOI measurement capability. A total of six minimodules were provided in three different cell/interconnect/backsheet combinations. Sandia characterized these minimodules using methods developed over two decades specifically for the outdoor characterization of full-size photovoltaic modules. This report documents the characterization results, summarizes key observations and tabulates the processed data for comparison to results provided by other characterization labs.
Anti-reflective coatings (ARCs) are commonly applied to commercial modules to reduce reflection losses and improve energy harvest. Relative performance at low incidence angle is often indistinguishable between different modules and it is only at high incidence angle that performance becomes differentiated. It is also precisely in this range that accurate measurements are the most difficult to obtain, complicating efforts to compare the benefits of different coatings. In this study, the performance of multiple commercial modules with different coatings were compared. A differential approach was employed, facilitating relative comparisons between test devices and a common reference. Using this method, performance differences at high incidence angles could be visualized and quantified. Differential analysis was extended to multiple system performance models in order to predict and quantify potential improvements in annual energy harvest. Improvements were observed upwards of 1% seasonally and 0.5% annually for the best performing coatings. 10° fixed tilt systems were seen to potentially benefit the most from ARCs, while single axis trackers benefitted the least.
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.
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
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 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.
Determination of module temperature coefficients for voltage, current and power requires measuring the average of cell temperatures. Conventional practice is to place thermocouples or resistive temperature devices (RTDs) at a few locations on a module's back surface and to average the readings, which may not accurately represent the average temperature over all cells. We investigate the suitability of averaging RTDs, which measure average temperature along a 1m length, to accurately measure the average cell temperature when determining temperature coefficients outdoors.
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.
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°.
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.
Reflection losses from a PV module become increasingly pronounced at solar incident angles >60°. However, accurate measurement in this region can be problematic due to tracker articulation limits and irradiance reference device calibration. We present the results of a measurement method enabling modules to be tested over the full range of 0-90° by articulating the tracker in elevation only. This facilitates the use of a shaded pyranometer to make a direct measurement of the diffuse component, reducing measurement uncertainty. We further present the results of a real-time intercomparison performed by two independent test facilities ∼10 km apart.
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.).
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.
The soiling losses on high concentrating photovoltaic (HCPV) systems may be influenced by the spectral properties of accumulated soil. We 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. Moreover, 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.
IEEE Standard 1547-2003 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.
