This work investigates several photovoltaic (PV) modules that have shown signs of metal contact corrosion due to field exposure in a hot and humid climate. This includes two multicrystalline silicon aluminum back surface field systems with 10 and 14 years of exposure and one monocrystalline silicon passivated emitter and rear cell system with four years of exposure. A comprehensive, multiscale characterization process is used to evaluate these PV modules in great detail. Current-voltage (I-V), Suns-V-OC measurements, electroluminescence imaging, infrared imaging, and ultraviolet fluorescence imaging were performed, and locations of interest were cored and analyzed using cross-sectional scanning electron microscopy (SEM). A rigorous, quantitative analysis procedure for the cross-sectional SEM images is proposed and implemented. Careful characterization does reveal that some of these PV modules do indeed exhibit the same classic signs of acetic-acid-based corrosion of the glass frit that is present at the silver/silicon interface, which have been observed previously in PV modules exposed to damp heat in an environmental chamber.

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.

In this work, a multiscale characterization and multimodal analysis approach is applied to silicon photovoltaic (PV) modules installed in the field. This approach links observed performance degradation to specific loss mechanisms (i.e., optical, recombination, resistive) and, ultimately, to root causes (i.e., changes in chemistry and/or microstructure). A key objective of this approach is the use of or, where needed, development of high-throughput, information dense data streams and the use of automated or semi-automated data analysis pipelines to remove subjectivity, improve reproducibility, and ensure scalability in both data collection and analysis. This work will present the application of this approach to a diverse collection of different PV modules installed at multiple sites, including lessons learned for each data stream and observations related to specific cell and module technologies.

This paper presents the preliminary results and findings of the four operational Floating PV systems across the USA. At each site, temperature of five PV modules located at North-West, North-East, Middle, South-West, and, South-East have been monitored through the Resistant Temperature Detector (RTD) sensors. Three RTDs were attached to each PV module on the rear-side along the diagonal at top, middle and bottom cells. The preliminary results reveal wide temperature differences among the inter and intra PV modules. Besides this, wave pattern temperatures were observed in a few PV modules. The final results, findings, and, factors responsible will be investigated during the next few months.

As the solar energy industry expands, the reliability and lifespan of photovoltaic (PV) modules have become increasingly important to ensure commercial viability for large-scale applications. To improve reliability and performance, it is necessary to better understand modes of failure through accelerated aging tests, which can identify degradation mechanisms that take a long time to manifest. This work investigates contact corrosion of fielded PV modules using a multi-scale analytical approach. Current-voltage (IV) and Suns-VOC measurements, electroluminescence (EL) imaging, Infrared (IR) imaging, and Ultraviolet Fluorescence (UVF) photography imaging were performed on multicrystalline silicon (multi-Si) and monocrystalline silicon (mono-Si) modules installed in a hot and humid climate. Subsequently, locations of interest were cored from the modules and analyzed using cross-sectional scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS).

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, VOC. 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.

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. PID‐impacting factors and limitation solutions are finally reported and a state of the art on PID modeling is presented.

Photovoltaic (PV) plant owners usually install PV arrays that are larger than the inverter's rated capacity. With a DC to AC ratio greater than unity, the PV array occasionally operates at a sub-optimal point imposed by the inverter. This is common practice in the USA, and is known as ‘clipping.’ Clipping may be implemented by operating the array at voltages below the maximum power point (MPP), or more commonly, above the MPP. Advantages of clipping operation are the utilization of an inverter's full capacity and improved financial break-even time. Regulatory requirements may also mandate reduced power output from an array in a forced clipping situation known as curtailment. However, the long-term impact on the PV array's life, array degradation, aging, hot spots, and module warranty has not been adequately investigated for prolonged off-MPP operation. This paper presents preliminary studies of the potential long-term impact of clipping on the PV array beyond energy production. For this study, the module and string level data, primarily through I-V curves and IR imaging, is investigated along with analysis of inverter electrical data. This preliminary work shows that the PV array exhibits significantly different temperature signatures if operated below the maximum power point as opposed to above, conditions which could be experienced when clipping. In addition, the initial data revealed unique IR imaging patterns: checkerboard patterns at voltages below the MPP and uniform elevated temperature patterns at voltages above the MPP.

The intentional removal of one or more photovoltaic modules from a string, thus shortening the length of the string relative to others within the array, may occur for a variety of reasons. The result is a mismatch in string length which our previous work has shown to impact the operation of the array by 1) shifting the ideal maximum power point of the array, and 2) inducing reverse currents in the shortened strings at VOC, a condition experienced by arrays under normal operation and during some maintenance activities. This work takes the experimentally verified simulation results of our previous small-scale studies and expands the simulations to elucidate behaviors at commercial and utility scales.

This paper presents a Machine learning-based algorithm to filter the time-series I-V curves collected from a PV plant. The filter’s objective is detecting and segregating the normal looking I-V curves from the abnormal ones. A non-linear Machine learning regression model was used for this purpose. Initially the model is trained on the labeled data and then tested on a unknown data. The proposed model is trained and tested on the time-series I-V curves of experimental PV strings installed in the field. The obtained model coefficients, results are discussed in the paper.

The intentional removal of one or more photovoltaic modules from a string, thus shortening the length of the string relative to others within the array, may occur for a variety of reasons. The result is a mismatch in string length which our previous work has shown to impact the operation of the array by 1) shifting the ideal maximum power point of the array, and 2) inducing reverse currents in the shortened strings at VOC, a condition experienced by arrays under normal operation and during some maintenance activities. This work takes the experimentally verified simulation results of our previous small-scale studies and expands the simulations to elucidate behaviors at commercial and utility scales.

This paper presents the principles behind the formation of current vs. voltage (IV) curves of a solar photovoltaic (PV) array. More than that, the inherent relationship existing between the strings of the PV array and rows of its IV curve is revealed. Explaining why IV curves always subscribe to a 'staircase' shape forms the dominant part of this paper. The findings going to help the PV instructors and teachers explain the IV curves in a better way, and PV analysts now can visualize them better than before. More importantly, findings are presented using graphical illustrations and plots. Hence, laborers, beginners and people with no mathematical background would understand the same way the people already working in the PV.

This paper proposes a new concept to detect the abnormal profiles of a grid-tied PV plant. Continuous measurement of many parameters and storage in the database is a routine task performed by any commercial Grid-tied PV plant. Detecting the abnormalities in the operation of PV plant is an import part of the reliable operation of the PV plant. Operational factors like electrical and non-electrical faults result in 'abnormal' profiles. However, non-operational factors like interruptions in the data transfer protocols found filling the database with 'corrupt' data leading to the 'abnormal' profiles. Detecting 'abnormal' profiles is crucial to the operation of PV plant. A new concept of comparing the daily profiles of a set of parameters and labeling a day normal or abnormal is proposed in this paper. The methods are programmed to detect the data on a given day is 'normal' or 'abnormal.' Recorded data from a 6.2 kW grid-tied PV plant is used for validating the proposed methods. A sample dataset and proposed methods can be downloaded at https://ieee-dataport.org/authors/manjunathmatam.

This paper presents the shortcomings in existing methodologies used for calculating the shunt resistance from the current vs. voltage (IV) curves collected at the indoor lab under controlled conditions or the outdoor under natural conditions. This paper mainly presents the inverse slope methodology and shortcomings surrounding it. Shunt resistance is one of the critical parameters for detecting the low power faults like cracks in the modules caused by extreme conditions. The findings were validated on the IV curves of a PV module from indoor tests and a string from outdoor tests collected at stable conditions. The findings of this paper open a new window of opportunity to search for new calculation methodologies.

This paper proposes to perform certain integrity checks and balances to omit the wrong data in the monitoring of a solar PV plant. Further, these checks and balances are segregated into three types: basic, specific, and pattern checks. The former is performed on the data collected from all the types of sensors. However, the second check is performed on the data collected from the specific instruments. These checks are specific to the site, instrument, parameter, etc. The third check verifies the shape of profiles between the data of different sections of the PV system. For the data-inclusion/deletion purpose, the parameters of PV plant are segregated into a triangle-hierarchy of highest-least priority. Some of the proposed checks are performed on the raw data collected from a grid-tied 271 kW PV plant and 6.4 kW test PV plant. The results have indeed identified some of the bad data and validated the proposed checks.

Photovoltaic (PV) plants operating under the partial shade condition show an imbalance in the array irradiance and produce less output power. To counteract this problem, reconfigurable PV array or dynamic PV array (DPVA) for changing the inter-connections of PV modules to balance the irradiance distribution has been proposed previously. This study introduces a new strategy, the maximum and minimum (M-2) algorithm, to identify global maximum irradiance configuration with a minimal number of interchanges among the PV modules. For the implementation of DPVA, this study introduces a double pole double throw (DPDT) switch network (SN) with less switch-count compared to a conventional SN. Simulations of PV array have been carried out on a 9 x 9 size PV array. Results are compared with the previously reported algorithms. Further, cost-benefit analysis of a 10 kW(P) grid-tied DPVA plant has been presented. Experimental tests on 4 x 2 size DPVA under different shade conditions are conducted to validate the proposed algorithm and DPDT SN.

As the photovoltaics industry matures the methods for monitoring and responding to power loss events is also maturing. For researchers to develop advanced algorithms to detect and notify plant owners of actual failures, and potential failures, reliable methods need to be developed to emulate field failures. This work discusses the development and characterization of three reliable methods for replicating power loss events in modules, and strings for outdoor field testing. Experimental methods were developed to emulate soiling, within module interconnection failures, and cell cracks. The objective of the work is to develop well characterized methods for inducing power loss such that data sets can be generated that can be used to develop advanced algorithms for power loss detection, root cause analysis, and prognostic notifications.

This paper introduces an algorithm to identify the global maximum power point (GMPP) of a solar Photovoltaic (PV) plant while operating under the partial shade condition (PSC) or fault condition (FC). Conventionally a complete current vs. voltage (or I-V) curve of the faulty PV array is swept to identify the GMPP. However, this paper proposes that a part or 'region of interest' of the I-V curve would be sufficient to identify the GMPP, and there is no need to sweep complete I-V curve. For verification purposes, realtime experimental tests were conducted.

A popular method to extract maximum power from a solar PV array is the direct connection of a DC/DC converter to the PV array. It is known as Maximum Power Point Tracking (MPPT) technique. In this approach, the PV array is perturbed at a fractional voltage and few tens of kHz frequency. Drawbacks in this approach of maximum power extraction include oscillations in the DC voltage, reduced conversion efficiency and frequent maintenance of the converters (owing to the frequent failure of electrolytic capacitor), which makes it unsuitable to rural area PV applications. This paper proposes Dynamic PV array (DPVA) approach for extracting maximum power from PV array. In this approach, a switch-network of semiconductor switches or electrical relays is integrated into the PV array to choose a matching-configuration for the load. The absence of high frequency operation, oscillations in the DC voltage and power processing stages are some inherent advantages of this approach. This paper presents a procedure to design a specific size Dynamic PV array, such that, it produces MPP or close to MPP power at all load conditions. Further, a mathematical relationship between the size of DPVA and the Minimum Output Power (MOP) it can produce is derived. Simulations and a six-module experimental tests are conducted to validate the derived relation.