Publications

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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.

Degradation and partial shading impact the long-term reliability and power production of photovoltaic (PV) modules and power plants. Time-series power (Pmp) and current–voltage (I-V) curve datastreams from PV modules enable a remote diagnostic approach to quantify active degradation mechanisms and identify partial shading. We study three to nine years of these datastreams, including 3.6 million I-V curves and 36 million Pmp values, from eight PV modules, four each of double-glass and glass-backsheet module architectures, located in three distinctly different Köppen-Geiger climate zones, to determine the module's performance loss rates (PLR), identify active degradation mechanisms and power loss modes, along with partial shading by local objects. Considering both module architectures, PLR results indicate that the BSh climate zone is the most aggressive for module degradation, while the Alpine ET zone is the mildest climate. PLR of double-glass modules located in BWh and BSh climate zones are different due to the significantly greater uniform current loss (ΔPIsc) for double-glass modules in BSh, at a 5% significance level. Power loss for four out of five modules located in the BWh and BSh climates are dominated by uniform current degradation. Statistical analysis of multistep I-V curves detects partial shading experienced by three studied modules with details of the shading profile, the shading Poynting vector diagram for the obstacle's relative position, shading scenarios, and duration. This work demonstrates how remote monitoring and diagnosis of Pmp & I-V time-series of modules can provide quantitative operations and maintenance insights into system performance, degradation mechanisms, and shading.

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Network structural equation modeling has been used for degradation modeling of glass/backsheet (GB) and double glass (DG) PERC PV minimodules, made by CSI and CWRU. The encapsulants used were ethylene vinyl acetate (EVA) and polyolefin elastomer (POE). The exposures included modified damp heat (80°C and 85% relative humidity), with and without full spectrum light. Each exposure cycle consists of 2520 hours, 5 steps of 504 hours each. The data from I-V and Suns-Voc was used in the analysis. We observe that most DG minimodules exhibit stability in power with exposure time and GB minimodules by CWRU showed a power loss of 5-6% on average due to corrosion.

We present the application of FAIR principles to photovoltaic time series data to increase their reusability within the photovoltaic research community. The main requirements for a "FAIRified"dataset is to have a clearly defined data format, and to make accessible all metadata for this dataset to humans and machines. To achieve FAIRification, we implement a data model that separates the photovoltaic data and its metadata. The metadata and their descriptions are registered on a data repository in a human and machine readable format, using JSON-LD. Also, secure APIs are developed to access photovoltaic data. This approach has long term scalability and maintainability.

To assess the reliability of PERC cells compared to Al-BSF in a commercial setting minimodules with cell and encapsulant combinations are compared in accelerated exposure. In both modified damp heat and modified damp heat with full spectrum light exposures, white EVA samples showed a higher susceptibility for metallization corrosion degradation than all other encapsulants. Al-BSF cells in particular showed higher power loss than PERC cells with white EVA. It was observed that the degree of degradation had a strong significance on the manufacturer of the white EVA encapsulant. In both exposures the encapsulant was a much stronger predictor of degradation than cell type. For modules with the same encapsulant, PERC cells showed the higher performance or were comparable to Al-BSF cells for all but one case.

Cell cracking in PV modules can lead to a variety of changes in module operation, with vastly different performance degradation based on the type and severity of the cracks. In this work, we demonstrate automated measurement of cell crack properties from electroluminescence images, and correlate these properties with current-voltage curve features on 35 four-cell Al-BSF and PERC mini-modules showing a range of crack types and severity. Power loss in PERC modules was associated with more total crack length, resulting in electrical isolation of cell areas and mild shunting and recombination. Many of the Al-BSF modules suffered catastrophic power loss due to crack-related shunts. Mild power loss in Al-BSF modules was not as strongly correlated with total crack length; instead crack angles and branching were better indicators of module performance for this cell type.

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Modeling and predicting snow-related power loss is important to economic calculations, load management and system optimization for all scales of photovoltaic (PV) power plants. This paper describes a new method for measuring snow shedding from fielded modules and also describes the application of this method to a commercial scale PV power plant in Vermont with two subsystems, one with modules in portrait orientation and the other in landscape. The method relies on time-series images taken at 5 minute intervals to capture the dynamics of module-level snow accumulation and shedding. Module-level images extracted from the full-field view are binarized into snow and clear areas, allowing for the quantification of percentage snow coverage, estimation of resulting module power output, and temporal changes in snow coverage. Preliminary data from the Vermont case study suggests that framed modules in portrait orientation outperform their framed counterparts in landscape orientation by as much as 24% energy yield during a single shedding event. While these data reflect a single event, and do not capture snow shedding behavior across diverse temperature and other climatic conditions, the study nonetheless demonstrates that 1) module orientation and position in the array influence shedding patterns; 2) the start of power production and bypass diode activation differ for portrait and landscape module orientations at similar percentages and orientations of snow coverage; and 3) system design is an important factor in snow mitigation and increased system efficiency in snowy climates.

Modeling and predicting snow-related power loss is important to economic calculations, load management and system optimization for all scales of photovoltaic (PV) power plants. This paper describes a new method for measuring snow shedding from fielded modules and also describes the application of this method to a commercial scale PV power plant in Vermont with two subsystems, one with modules in portrait orientation and the other in landscape. The method relies on time-series images taken at 5 minute intervals to capture the dynamics of module-level snow accumulation and shedding. Module-level images extracted from the full-field view are binarized into snow and clear areas, allowing for the quantification of percentage snow coverage, estimation of resulting module power output, and temporal changes in snow coverage. Preliminary data from the Vermont case study suggests that framed modules in portrait orientation outperform their framed counterparts in landscape orientation by as much as 24% energy yield during a single shedding event. While these data reflect a single event, and do not capture snow shedding behavior across diverse temperature and other climatic conditions, the study nonetheless demonstrates that 1) module orientation and position in the array influence shedding patterns; 2) the start of power production and bypass diode activation differ for portrait and landscape module orientations at similar percentages and orientations of snow coverage; and 3) system design is an important factor in snow mitigation and increased system efficiency in snowy climates.

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