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Seigneur, Hubert

Publications and source records attributed to Seigneur, Hubert.

Field Study of Nighttime Leakage Currents in Bifacial PV Modules: Correlation with Atmospheric Electric Field Data

Leakage currents measured on PV modules in the field originate from a potential difference between the modules' frame and the cells. They can be a relative indicator of Potential-Induced Degradation (PID) severity, especially when comparing the same module design in a different environment. As modules are not operating at night, no leakage current should be observed but our team has reported several events of nighttime leakage currents on bifacial PV modules. These events have been firstly observed during a thunderstorm that are characterized by strong atmospheric electrical field values. This lead us to believe that nighttime leakage currents could originate from the atmospheric electric charges. In this paper, we correlate nighttime leakage currents measured on bifacial PV modules with field mill data to identify the origin of nighttime leakage currents. Our results show that so far, no leakage currents at night occur when the atmospheric electric field is between 0 and 150–200 V/m (standard value for fair weather). As soon as the atmospheric electric field is out of this range, leakage currents are observed with or without rain involved. This suggests a transport of charged particles from the atmosphere to the modules' frame. A combination of heavy rain with strong atmospheric electric field results into high nighttime leakage currents with a magnitude up to 8 times higher than what observed during the day with -1500V applied. This is explained by an easier transport of the charged particles through the water droplets. Based on these results, leakage currents observed during the day might not be only due to the inherent potential difference between the frame and the cells depending on the atmospheric electric field activity. We believe that it should be taken into account in PID studies.

14 SOLAR ENERGY↗

Susceptibility to polarization type potential induced degradation in commercial bifacial p-PERC PV modules

Potential induced degradation (PID) is a reliability issue affecting photovoltaic (PV) modules, mainly when PV strings operate under high voltages in hot/humid conditions. Polarization-type PID (PID-p) has been known to decrease module performance quickly. PID-p can be reduced or recovered under the light in some cases, but this effect, as expected, would be less pronounced on the rear side of bifacial PV modules receiving lower irradiance. As bifacial PV modules are projected to dominate the PV market within the next 10 years, it is crucial to understand the PID-p issue in bifacial modules better. In this study, we performed indoor PID testing to induce PID-p on 14 commercial bifacial p-PERC modules with three different module constructions from three manufacturers. Here, four rounds (+ve and –ve polarities for front and rear sides) of PID testing are done at 25°C, 54% relative humidity (RH) for 168 h using the aluminum foil method. Each module side (front cell side and back cell side) is tested individually under both negative and positive voltage bias. The results show that the highest degradation of 32% in maximum power (Pmax) at standard test conditions (1000 W/m 2 ) and 51% at low irradiance (200 W/m 2 ) has been observed in some cases. Recovery under sunlight is also done, and outcomes show a near-complete recovery in Pmax. This study presents an extensive experimental methodology and a detailed analysis to systematically and simultaneously/sequentially evaluate multiple construction types of bifacial modules to the PID-p susceptibility and recovery.

14 SOLAR ENERGY↗

A study of Cell Cracks Formation During Freight Shipping : Monitoring Shock and Temperature in Real-Time & Assessing Damages With Pre and Post-Transit Characterizations of PV Modules

The solar photovoltaic (PV) industry often experiences module damage during transportation. PV modules stacked horizontally and strapped on wooden pallets may develop failures impacting their efficiency (glass shattering, cracks, frame indentation, etc.), especially when modules are not packed by professionals. The appearance of failures during the shipment from one laboratory to another can be detrimental to research studies. In this study, we tested a reusable plastic pallet designed to ship modules vertically. Five technologies of commercial PV modules were shipped together from Arizona to Florida including: glass/glass bifacial modules (framed and frameless), glass/transparent backsheet bifacial modules and glass/white backsheet modules (framed). Each module technology has a different physical size. Some modules had pre-existing cell-cracks allowing for the study of cell-crack formation and propagation during shipment. Dark current-voltage (I-V), light I-V and electroluminescence characterization were performed before and after shipment. A datalogger was used to monitor shocks and ambient temperature throughout the shipment and identify when the modules were more susceptible to damage. The modules were tilted upon receipt and the pallet were damaged but with no shattered modules. Time series shock data provided by the datalogger were used to determine potential responsible events. Our results reveal a few new post-transportation cracks for some modules. Modules parameters before and after shipment are also compared regarding the module constructions and their position in the pallet.

14 SOLAR ENERGY↗

Review of Potential–Induced Degradation in Bifacial Photovoltaic Modules

Bifacial modules are increasingly deployed in the field and are expected to represent half of the market share within 10 years. Their rear structure differs from monofacial modules to allow additional light absorption. However, it brings new reliability challenges to address. In particular, the risk of potential-induced degradation (PID) is increased as both module sides are impacted. Different PID processes have been identified in the literature: shunting type (PID-s), polarization type (PID-p), Na penetration type, and corrosion type (PID-c). Their occurrence depends on the photovoltaic system configuration as well as the module's materials. Apart from PID-s, PID processes are not well understood and extensive research is needed to elucidate the PID scenario and underlying mechanisms. Herein, current knowledge about PID processes and their impact on the main bifacial modules in the market are gathered with the aim to guide future research. Bifacial module technologies and leakage current paths leading to PID are described. Indoor and outdoor PID testing methods are detailed. For each bifacial module technology, the PID processes are investigated with their indicators, mechanism and recovery process. Furthermore, PID-impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.

14 SOLAR ENERGY↗

Reliability Evaluation of Bifacial and Monofacial Glass/Glass Modules with EVA and non-EVA Encapsulants

The market share for bifacial modules is projected to be doubled from 30% to 60% in the next ten years. For the monofacial crystalline silicon glass/backsheet (G/B) modules, extensive reliability data has been available for over 40 years. However, practically little/no long-term field or accelerated reliability test data is available for the new generation glass/glass (G/G) bifacial modules and glass/transparent (G/T) bifacial modules. Therefore, the primary motivation of this project was to identify the reliability strengths and weaknesses of new generation G/G modules compared to G/B modules. In this 3-year project, the goal was to objectively recommend the best construction materials for the new generation G/G (bifacial) modules through a systematic experimental approach with appropriate tasks including: Evaluation of field retrieved old-generation G/G modules; Inspection of new-generation G/G modules installed in the plants; Evaluation of new-generation G/G, G/B and G/T modules using EAST (Extended Accelerated Stress Testing), CAST (Combined Accelerated Stress Testing) and FAST (Field Accelerated Stress Testing); and, dynamic literature search and review. Major accomplishments and outcomes of this project are: Accomplishments: Evaluated more than 60 field retrieved modules and constructed and characterized more than 135 mini-modules with three substrate types (G, B, and T), two encapsulant types (EVA and POE), and two cell types (monofacial and bifacial) as well as evaluated more than 30 commercial G/G and G/B modules; Subjected all the modules to multitude characterization tests and various indoor and outdoor accelerated stress tests including FAST (Field Accelerated Stress Testing), EAST (Extended Accelerated Stress Testing), and CAST (Combined Accelerated Stress Testing) to identify and correlate the failure modes in both field and lab tests. Outcomes: Based on the accelerated test results and handling/mounting experience obtained in this project, the recommended best construction for the glass/glass modules is: “Framed GG modules with cut-cells and POE encapsulant (UVpass front; UVpass back).” However, from a statistical and manufacturing point of view (along with stakeholders surveys), the following cautionary notes are added to the above-mentioned recommendation: (i) Cut cells could introduce a higher level of manufacturing issues, including a higher number of cell interconnects; (ii) POE encapsulant is more expensive than EVA and could present a delamination risk and lower throughput during manufacturing due to lower adhesion strength. Other encapsulants, such as coextruded EPE (EVA/POE/EVA), are also recommended to be investigated. The potential public benefit of the proposed project is to present the strengths and weaknesses of glass/glass modules, so an informed procurement decision can be made.

14 SOLAR ENERGY↗

LCOE reduction through proactively optimized monitoring of PV Systems (Final Technical Report)

The project demonstrates the value proposition for a high-resolution monitoring system (HRMS) with diagnostic-prognostic capability and determine its impact on LCOE. The HRMS differs from conventional monitoring systems in a number of ways. First it will include the capability to automatically measure IV curves at the string and module levels. This provides a much richer view into the DC performance of the PV system and allows classification of many typical failure and degradation modes. Second, it will incorporate software capable of quantifying power and energy losses in the field as well as define the location and mechanism of the power and energy loss. Moreover, we aimed to deliver a prognostic system that is capable of predicting certain failures before they occur and giving system operators the opportunity to more efficiently plan operations and maintenance (O&M) activity in order to lower costs and increase yield over the life of the system. The research identifies cost targets required for different monitoring stages, including at the string combiner, at the individual string, and at the module level, to lower the levelized cost of energy (LCOE). Finally, a comprehensive guide determines the value PV monitoring brings to PV field operations. The guide assists plant operators in maximizing value from existing plants and identify the trade-offs of different monitoring solutions for future plants depending on the size, location, and expected system lifetime.

14 SOLAR ENERGY↗

Onymous early‐life performance degradation analysis of recent photovoltaic module technologies

Abstract 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.

14 SOLAR ENERGY↗

Impact of Measured Spectrum Variation on Solar Photovoltaic Efficiencies Worldwide

In photovoltaic power ratings, a single solar spectrum, AM1.5, is the de facto standard for record laboratory efficiencies, commercial module specifications, and performance ratios of solar power plants. More detailed energy analysis that accounts for local spectral irradiance, along with temperature and broadband irradiance, reduces forecast errors to expand the grid utility of solar energy. Here, ground-level measurements of spectral irradiance collected worldwide have been pooled to provide a sampling of geographic, seasonal, and diurnal variation. Applied to nine solar cell types, the resulting divergence in solar cell efficiencies illustrates that a single spectrum is insufficient for comparisons of cells with different spectral responses. Cells with two or more junctions tend to have efficiencies below that under the standard spectrum. Silicon exhibits the least spectral sensitivity: relative weekly site variation ranges from 1% in Lima, Peru to 14% in Edmonton, Canada.

energy yield↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Many of these power plants have spatiotemporal coherence that can be utilized for improving model accuracy. We have demonstrated in this paper the FAIRification of spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. Going further, we have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. To solve the issue of data missingness, we propose the use of St-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗

PyPVRPM: Photovoltaic Reliability and Performance Model in Python

The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.

97 MATHEMATICS AND COMPUTING↗

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗

Mismatch losses in a PV system due to shortened strings

Numerous events may require intentional removal of one or more photovoltaic modules from a string, shortening the length of the string relative to others within the array, resulting in a string length mismatch. The impact of such a mismatch is not well understood either in measurable operational effects (voltage, current, power) or in the potential effects on long-term module health. It is impractical to solely approach this problem experimentally due to the size and complexity of arrays that may experience string length shortening. Here this work presents simulations, validated through limited field experiments on a two string array, providing a basis from which more complex arrays and scenarios may be explored. Refinement of the simulation achieves an overall error in IMPP for the nominal (S 1 ) and test strings (S 2 ) between the simulation and experimental values, through all test conditions, of +0.35 ± 1.46% and -0.36 ± 1.58% respectively. Shortening one of two strings by one module results in a power loss greater than the power contribution of the module alone (1.29 module equivalents); the impact increases through the maximum test case of a six module mismatch with a power loss equivalent to more than 11 modules. The impact of using string-end blocking diodes is presented with an emphasis at the array maximum power point and at open circuit. Implications are discussed for arrays of higher complexity.

14 SOLAR ENERGY↗