Ryan M. Smith

This study investigates the polarization‐type potential‐induced degradation (PID‐p) of bifacial glass/glass ‐type passivated emitter rear contact ( ‐PERC) modules in the field and their recovery behavior. Modules were installed with three mounting configurations providing different albedo conditions. System voltage ( 600, 1500, and +1500 V) was applied to the cell circuits, with respect to the grounded module frames. No degradation was observed for positively biased modules, but PID‐p was identified on the rear side when cells are negatively biased, with maximum power dropping during the first days and stabilizing at values up to 8% loss. Electroluminescence images revealed a variation of the cells' PID‐p susceptibility within a module. Three parameters were shown to impact the degradation rate: rear albedo light, voltage, and wetness conditions. Degraded modules were recovered either by (1) a positive bias (+1500 V), (2) outdoor illumination with the front side facing sun, (3) outdoor illumination with the rear side facing sun, or (4) dark storage. A recovery pattern was identified with – parameters decreasing to a local minimum before increasing to full recovery. The proposed mechanism is based on the band bending at the rear ‐type Si/AlO interface, going from inversion to depletion and accumulation states. Full recovery was achieved in 2–7 h for the modules recovered with the rear side facing sun, four to eight nights for the modules positively biased at night, and 10–20 days for the modules with the front side facing sun. Dark storage showed slower recovery rates as – parameters were not improving even after 1 month. The recovery rates were correlated with the net Coulombs transferred during the preceding PID stress: When more Coulombs are transferred during the degradation, the extent of degradation is greater, leading to slower recovery rates.

Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m², 500–600 W/m², and 900–1000 W/m². These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m²) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.

Domestic water heaters traditionally use natural gas or electric resistance to heat stored water. A gas water heater relies on a non-renewable resource, while an electric water heater might rely on electricity generated by a non-renewable resource. This study analyzes the performance of an electric water heater featuring a novel heating element design based on a positive temperature coefficient (PTC) material powered directly by solar photovoltaic (PV) modules in a northern latitude installation. The project analyzes the operation of two different design temperatures of the PTC heating elements (50 °C, and 70 °C) when fed by three solar PV panels during the spring in the high-latitude location of Anchorage, Alaska (61.2° N). Our results show that both design temperatures of the PTC heating elements are able to achieve self-regulation at a sufficient and safe operating temperature for a domestic use case. Analysis of water heater performance directly connected to PV power showed that the PTC-equipped water heater had a limited period of heating when sufficient solar irradiance is available. Because of this, restrictive use of the water heater might be necessary during periods of non-daylight hours to preserve hot water in an insulated tank. However, this PV-to-PTC setup could be effectively used in industrial, commercial, and research settings.

This study examines the susceptibility of bifacial glass/glass passivated emitter and rear cell (PERC) modules to potential-induced degradation-polarization (PID-p) in the field. While there are several studies showing PID-p occurring on both front and back faces of bifacial PERC in accelerated tests, we address the yet unclarified behavior in fielded modules. We examine the effects of mounting configuration; specifically, comparing modules mounted near ground and in elevated ground rack configurations. Modules with the cell circuit in −1500 V system voltage configuration, whether mounted on racks about 30 cm above the ground or elevated 2 m high showed mean degradation of 4.5% to 6% in power under standard test conditions over about 2.5 weeks as measured from the front side of the module. This extent of degradation remained sustained for a duration of about 6 months analyzed. Average daytime temperatures of modules in the various mounting configurations were similar and therefore judged to be insufficient to be a primary influence for the modest PID-p rate differences that we observed among mounting configurations. Increased leakage current in the morning suggests morning dew was sustained longer on modules near the ground measured over six months which would be expected to increase the PID-p rate over the long term. However, the main difference seen between the modules on the various mountings during the initial period with up to 6% mean degradation by PID-p was the approximately two times the irradiance from albedo on the rear of modules mounted in elevated ground rack compared to those on the near ground rack. This difference in incident albedo led to a modestly reduced rate of the development of PID-p of the modules on the elevated ground rack. The difference is attributed to the dissipation of PID-p-causing electrical charge by the albedo incident on the module rear. The behavior could be modeled by a sigmoidal equation with consideration of the differences in the insolation on the module rear.

In this paper, we use deep learning models to detect and classify various data objects within photovoltaics (PV) module datasheets stored in pdf or other image file formats. We seek to differentiate between regular text, table, header, footer, module drawing, document header, IV curve, PV curve, warranty graph, module image, and icon in order to automate the extraction of useful metadata from datasheets. Our work investigates whether existing computer vision models such as Detectron2 and YOLOv8x can be leveraged to accurately localize and classify the various data types with and without transfer learning. The models were trained on 57 datasheets with multiple pages or 169 pages in total. Detectron2 achieved an overall mAP50-95 of 0.78 without transfer learning (600 epochs and 16 hours) and an mAP50-95 of 0.54 (60 epochs and 2 hours) with transfer learning. YOLOv8x achieved an mAP50-95 of 0.89 without transfer learning (1000 epochs and 2 hours) and an mAP50-95 of 0.9 (20 epochs and several minutes).

The deliberate removal of photovoltaic modules from a string can occur for various reasons encompassing maintenance, measurements, theft, or failure, reducing that string length relative to others when replacement modules are not available and there are not any viable alternative makes and models that could be inserted. This phenomenon, delineated in our prior experimentally validated research, manifests two significant effects: (1) a shift in the ideal maximum power point and (2) the induction of potentially substantial reverse currents in the shortened strings at open-circuit voltage, V_OC. However, the scalability and asymptotic limits of these observed behaviors concerning array size remained undetermined. In this study, we elucidate the operational dynamics of such arrays by manipulating two mismatch-contributing variables in simulated arrays of up to 900 strings: the number of removed modules per string (indicative of the level of mismatch, ranging up to 5) and the quantity of shortened strings (1 to 60). Simulation outcomes underscore that mismatch severity impacts array operation more than the proportion of shortened strings. This research delves into the practical ramifications of operating with shortened strings, including implications for low-irradiance operation and the manifestation of deleterious reverse currents (>35 A in specific cases), emphasizing the need for careful array configuration for optimal performance and safety in these implementations.

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.

This paper presents an energy efficient transmitter for multi-standard applications (IEEE802.15.4, BLE, 5Mbps) in ISM2.4GHz band. It incorporates a fully digital PLL with two point modulation to achieve upto 5Mbps data rate at 9.5mW power consumption (including all power management blocks) at 0dBm output power, leading to 1.9nJ/b efficiency. The proposed digital PLL uses a counter based area and power efficient re-circulating TDC, current reuse low area DCO using resistive tail, process compensated high speed divider, class-AB PA stages, and fully integrated on-chip LDOs. The entire transmitter occupies 0.35mm² Silicon area in a 65nm digital CMOS process.