Photovoltaic Module Technologies Research Articles

Polymer encapsulation impact on potential-induced degradation in PV modules revealed by a multi-modal field study

Potential-induced degradation is a significant issue affecting the performance and reliability of photovoltaic systems, particularly in large-scale installations. Understanding the mechanisms underlying the formation of potential-induced degradation is crucial for developing effective mitigation strategies and ensuring the long-term sustainability of solar energy technologies. During the inspection of a 1.2 MWp photovoltaic power plant, various imaging methods, electrical measurements, spectroscopic characterization methods, and monitoring data analyses were utilized and combined. We observed that two percent of the photovoltaic modules at the string ends exhibited the characteristic checkerboard pattern in infrared or electroluminescence imaging, implicating issues on twelve percent of all strings. This uneven distribution of potential-induced degradation-affected modules suggests additional key factors are at play. Investigations of the backsheet and ethylene-vinyl acetate using near-infrared reflectance analysis revealed that one backsheet type and two different ethylene-vinyl acetate types were present in the installed solar panels. Yet, only one type of ethylene-vinyl acetate correlated with potential-induced degradation. The same type also exhibited a higher rate of oxidative degradation. Scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed a significantly increased sodium ion content in the ethylene-vinyl acetate and glass of the potential-induced degradation-affected modules. Our findings highlight the crucial role of polymer encapsulation in the development of potential-induced degradation and underscore the importance of careful polymer selection in the design of photovoltaic module technologies.

Upright Pyramid Surface Textures for Light Trapping and MoOx Layer in Ultrathin Crystalline Silicon Solar Cells

In this work, ray tracing is used to investigate the optical characteristics of various surface structures in ultrathin crystalline silicon (c-Si) for solar cells. Ultrathin c-Si with a thickness of 20 μm is used as the substrate. The light trapping includes front upright pyramids with a molybdenum oxides (MoOx) anti-reflection (AR) layer. Planar ultrathin c-Si (without a MoOx AR layer and upright pyramids) is used as a reference. The wafer ray tracer was developed by a photovoltaic (PV) lighthouse to model the MoOx AR layer to reduce the front surface reflectance and impacts of the AR layer on ultrathin Si solar cells. The optical properties are calculated on the AM1.5 global solar energy spectrum across the 200–1200 nm wavelength region. From the absorbance profile, the photogenerated current density (Jph) in the substrate is also calculated with various surface structures. The front upright pyramids with the MoOx layer result in the largest absorbance enhancement due to the enhanced light scattering by the pyramids and MoOx AR layer. The Jph of 37.41 mA/cm2 is improved when compared to the planar ultrathin c-Si reference. This study is significant as it illustrates the potential of ultrathin c-Si as a promising PV module technology in the future.

Climate‐ and Technology‐Dependent Performance Loss Rates in a Large Commercial Photovoltaic Monitoring Dataset

Detailed knowledge of the performance of photovoltaic (PV) systems over their full lifetime is invaluable for evaluating their profitability and sustainability. PV systems are known to have gradually declining performance; for long‐term yield assessments, typically a performance loss rate (PLR) of −0.5% yr−1 is assumed. Herein, monitoring data of thousands of commercial PV systems is evaluated to determine how performance loss trends and PLR values are affected by operational climate, PV module technology, and other parameters. Using performance ratio (PR) measurements from almost 6000 PV systems, the long‐term trends in PR and overall PLR value are evaluated. Subsequently, the relation between climate, performance loss, and PLR for three different climate classification schemes is evaluated. Finally, how long‐term performance loss trends and estimated PLR values differ for PV module technology and other parameters are evaluated. The results show that in general, PV systems that have operated now for at least 3 but up to 25 years show a PLR of roughly −1% yr−1, indicating substantially higher performance loss compared to typical estimates used for new PV systems. Climate by itself does not seem to be the leading factor that determines overall performance loss trends or PLR values in the dataset analyzed.

Performance assessment of different photovoltaic module technologies in floating photovoltaic power plants under waters environment

The paper undertakes a novel study that aims to analyze the performance characteristics of ten monocrystalline or polycrystalline silicon modules employing different emerging technologies in waters environment. In this work, monitoring data were collected over a duration of one year using a multi-technology empirical platform within a floating photovoltaic power plant. The energy performance of different module technologies was evaluated using multiple performance metrics such as array yield, performance ratio, capacity factor, efficiency and energy density. By considering environmental variables such as irradiance, ambient temperature, and water temperature, the thermal behavior of photovoltaic modules under water surface deployment conditions is revealed. Furthermore, the multiple variable coupling analysis was conducted to determine the correlation between the performance metrics of various technology type modules and meteorological variables in waters environment. The results indicate that the energy performance and reliability of monocrystalline silicon modules using double-glass double-sided P-type PERC technology is superior to other technologies in waters environment, and the performance ratio and capacity factor reach 88.95 % and 15.04 %, respectively. The heterojunction with intrinsic thin-layer (HIT) technology module exhibits better thermal stability and holds an advantage in the deployment of limited water surface areas due to its higher energy density. Moreover, the performance ratio of floating photovoltaic systems shows a weak correlation with irradiance, and is more significantly affected by the negative correlation of ambient temperature than water temperature.

Real-time and modelled performance assessment and validation studies of PV modules operating in varied climatic zones

With the increasing adoption of solar energy as a sustainable power source, it is crucial to evaluate the performance of photovoltaic (PV) modules under diverse environmental conditions to ensure optimal energy production and system efficiency. Present work gives a comprehensive overview of performance assessment and validation studies conducted on different PV module technologies such as multi-crystalline silicon (mc-Si), cadmium telluride (CdTe), copper indium gallium selenide (CIGS), amorphous silicon (a-Si), heterojunction with intrinsic thin layer (HIT) and interdigitated back contact (IBC) operating under varied climatic conditions at different locations in India. To ensure accuracy and reliability, rigorous data collection and analysis methodologies were employed. The performance assessment has been computed through simulation using PVSOL software. Moreover, the performance ratio (PR) of all the PV module technologies was found to vary from 0.76 to 1.04. The present work validates the efficacy of the software as we have compared the computed results with real-time data obtained for all the PV modules, which were installed at NISE (National Institute of Solar Energy), Gurugram India. The performance ratio of all the PV module technologies has been evaluated through both the PVSOL and using real time data. The results show that the mean percentage change in PR values has been estimated approximately to be 2% in CdTe, CIGS, and a-Si modules technologies and 3% in mc-Si, HIT and IBC module technologies.

Impact of Voltage Temperature Coefficient on power prediction of four type silicon photovoltaic module technologies installed in real conditions in the north-central of Algeria

In this paper, attention has been paid to the importance of knowing the exact values of the temperature coefficients used in modeling of four different types of photovoltaic modules these modules are; monocrystalline silicon m-Si, polycrystalline silicon p-Si, amorphous silicon a-Si, and micromorphous silicon thin film μm-Si installed in outdoor conditions in north-central Algeria. The value of the temperature coefficients provided by the module manufacturer in the datasheet is obtained under specific conditions called the standard test conditions STC, but in reality, these conditions vary significantly if the modules are operated in real climatic conditions, this will lead us to recalculate these coefficients again to improve our model using a database collected over a period of one year obtained by our characterization bench of PV modules using a two diodes model. A comparison was made between the simulation and the experimental data of the selected modules using the new values of the calculated temperature and those given at STC conditions, the obtained results show that the use of these new calculated temperature coefficients leads to a reduction of the the Mean Relative error MRE on the annual power from 2 to 7% depending on the PV module's technology which shows the importance of knowing the real value of the temperature coefficients that will be used in the PV module and system modeling.

Performance of Monofacial and Bifacial Silicon Heterojunction Modules under Desert Conditions and the Impact of PV Soiling

The performance and reliability of photovoltaic (PV) modules in a desert climate depends, among other factors, on the solar irradiance, operating temperature, and soiling rate. Since the impacts of these environmental factors depend on the type of PV module technology, an assessment of the PV technology to be deployed in the desert climate is crucial for the bankability of PV projects. In this work, the indoor and outdoor performance of monofacial and bifacial silicon heterojunction PV module technologies were assessed. For the indoor measurements, a comparison of the current-voltage (IV) characteristics was performed at standard testing condition and at different temperatures. The two module technologies showed similar temperature coefficients and expected performance within the measurement uncertainty. Comparing the specific energy yield of the modules installed in the Outdoor Test Facility (OTF), the bifacial module showed a 15% higher energy yield than the monofacial module and is attributed to the contribution of the bifacial rear side, thanks to the reflected irradiance received by the bifacial module and the high albedo of 0.43 measured at the OTF. Moreover, the bifacial module was found to be less sensitive to the PV soiling than the monofacial module. The results showed that the frequency of module cleaning could be reduced for the bifacial module compared with the monofacial module, resulting in a remarkable decrease in the module cleaning cost and PV site Operation and Maintenance cost.

Holistic yield modeling, top-down loss analysis, and efficiency potential study of thin-film solar modules

A holistic simulation of a photovoltaic system requires multiple physical levels - the optoelectronic behavior of the semiconductor devices, the conduction of the generated current, and the actual operating conditions, which rarely correspond to the standard testing conditions (STC) employed in product qualification. We present a holistic simulation approach for all thin-film photovoltaic module technologies that includes a transfer-matrix method, a drift-diffusion model to account for the p-n junction, and a quasi-three-dimensional finite-element Poisson solver to consider electrical transport. The evolved digital model enables bidirectional calculation from material parameters to non-STC energy yield and vice versa, as well as accurate predictions of module behavior, time-dependent top-down loss analyses and bottom-up sensitivity analyses. Simple input data like current-voltage curves and material parameters of semiconducting and transport layers enables fitting of otherwise less-defined values. The simulation is valuable for effective optimizations, but also for revealing values for difficult-to-measure parameters.

Photovoltaics literature survey (no. 182)

Photovoltaics literature survey (no. 182)

Photovoltaic energy balance estimation based on the building integration level

The photovoltaic module building integration level affects the module temperature and, consequently, its output power. In this work, a methodology has been proposed to estimate the influence of the level of architectural photovoltaic integration on the photovoltaic energy balance with natural ventilation or with forced cooling systems. The developed methodology is applied for five photovoltaic module technologies (m-Si, p-Si, a-Si, CdTe, and CIGS) on four characteristic locations (Athens, Davos, Stockholm, and Würzburg). To this end, a photovoltaic module thermal radiation parameter, PVj, is introduced in the characterization of the PV module technology, rendering the correlations suitable for building-integrated photovoltaic (BIPV) applications, with natural ventilation or with forced cooling systems. The results show that PVj has a significant influence on the energy balances, according to the architectural photovoltaic integration and climatic conditions.

Using Machine Learning for Analysis a Database Outdoor Monitoring of Photovoltaic System

In this paper, a new method for analyzing a databaseofoutdoor monitoring of photovoltaic system using machine learninghas been proposed, a Photovoltaic (PV) module (150 w) located in Algiers has been monitored for 80 days and the obtained results have been analyzed.The researchers face many difficulties one of the most significant ones is in terms of collecting and analyzing the obtained results, especially for long period of time of monitoring. In this paper we proposea new methodto analyze the results by machine learningusing Support Vector Machine (SVM) Classifier. Insuch away, we regroup a data variable to multiclass for according and analysis using SVM. Whichhave presented thoroughly all the classificationsteps. Using method ofartificial intelligence (machine learning), recorded data, and thepower output for a given photovoltaic module (PV) technology, types, and small or large stations under any seasons itmakes analysis and processing easy. Themeasurementsofthisworkswere investigated based on the recorded data by acquisition (Keysight 34972A). The system takes measurements data from sensors in a database ready for analysis. The data was taken from the measurement system from 05h00to 21h00 with irradiation of 50 W/m2, which is a starting point, however in 0 to 50 W/m2the system cannot detect any photovoltaic effect. Results predict that the performance ratio (PR) from a Poly-crystallinePV module was around 85.28 % for a different season’s exposure and 727 point analyses at irradiation of 850-950 W/m2at the same time 14h00-15h00. The temperature of a photovoltaic PV module isas wellcalculated and compared with different irradiation and time.

Effect of Temperature and Wind Speed on Efficiency of Five Photovoltaic Module Technologies for Different Climatic Zones

The objective of this study is to investigate the effect of temperature and wind speed on the performance of five photovoltaic (PV) module technologies for different climatic zones of Pakistan. The PV module technologies selected were mono-crystalline silicon (MC); poly-crystalline silicon (PC); heterogeneous intrinsic thin-film (TFH); copper–indium–allium–selenide (TFC); and thin-film amorphous silicon (TFA). The module temperature and actual efficiency were calculated using measured data for one year. The actual efficiency of MC, PC, TFH, TFC, and TFA decreases by 3.4, 3.1, 2.2, 3.7, and 2.7%, respectively, considering the effect of temperature only. The actual efficiency of MC, PC, TFH, TFC, and TFA increases by 9.7, 9.0, 6.5, 9.5, and 7.0% considering the effect of both temperature and wind speed. The TFH module is the most efficient (20.76%) and TFC is the least efficient (16.79%) among the five materials. Under the effect of temperature, the actual efficiency of TFH is the least affected while the efficiency of TFC is the most affected. The actual efficiency of MC is the most affected and that of TFH is the least affected under the combined effect of wind speed and temperature. The performance ratio of TFC is the most affected and that of TFH is the least affected under the effect of temperature and the combined effect of temperature and wind speed. The performance of PV technology, under real outdoor conditions, does not remain the same due to environmental stresses (solar irradiance, ambient temperature, and wind speed). This study plays an important role in quantifying the long-term behavior of PV modules in the field, hence identifying specific technology for the PV industry in suitable climatic conditions.

Validation of Photovoltaic Spectral Effects Derived From Satellite-Based Solar Irradiance Products

The Satellite Application Facility on Climate Monitoring (CM-SAF) Spectral Resolved Irradiance (SRI) and National Renewable Energy Laboratory National Solar Radiation Database Spectral on Demand (NSRDB-S) satellite-based spectral irradiance products are tested here against benchmark data and models at seven ground stations: one in Spain for CM-SAF SRI and six in North America for NSRDB-S. Benchmarks include WISER spectroradiometers, spectra modeled from SolarSIM-G measurements, the First Solar model of spectral mismatch factor (SMM), and the SMARTS radiative code with two alternate input sources: AErosol RObotic NETwork (AERONET) and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis. The satellite products are tested in terms of their ability to estimate photovoltaic (PV) spectral effects for six PV module technologies. Spectra are also compared directly. CM-SAF SRI generally outperforms First Solar and “no spectral effects” benchmarks, except for cadmium telluride modules. For NSRDB-S, predictions of long-term spectral derate factors show less skill than for instantaneous SMMs. Spectra comparisons reveal systematic differences between NSRDB-S and benchmark spectra, likely due to the NSRDB-S treatment of aerosols. Meanwhile, the mean SMARTS spectra with AERONET and MERRA-2 inputs are in good agreement, showing promise for the use of MERRA-2 as input to clear-sky models.

Photovoltaic parameters estimation of poly-crystalline and mono-crystalline modules using an improved population dynamic differential evolution algorithm

<span>Photovoltaic (PV) parameters estimation from the experimental current and voltage data of PV modules is vital for monitoring and evaluating the performance of PV power generation systems. Moreover, the PV parameters can be used to predict current-voltage (I-V) behavior to control the power output of the PV modules. This paper aimed to propose an improved differential evolution (DE) integrated with a dynamic population sizing strategy to estimate the PV module model parameters accurately. This study used two popular PV module technologies, i.e., poly-crystalline and mono-crystalline. The optimized PV parameters were validated with the measured data and compared with other recent meta-heuristic algorithms. The proposed population dynamic differential evolution (PDDE) algorithm demonstrated high accuracy in estimating PV parameters and provided perfect approximations of the measured I-V and power-voltage (P-V) data from real PV modules. The PDDE obtained the best and the mean RMSE value of 2.4251E-03 on the poly-crystalline Photowatt-PWP201, while the best and the mean RMSE value on the mono-crystalline STM6-40/36 was 1.7298E-03. The PDDE algorithm showed outstanding accuracy performance and was competitive with the conventional DE and the existing algorithms in the literature.</span>

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

AbstractThe 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.

Prediction of photovoltaic power output based on different non-linear autoregressive artificial neural network algorithms

Prediction of power output plays a vital role in the installation and operation of photovoltaic modules. In this paper, two photovoltaic module technologies, amorphous silicon and copper indium gallium selenide installed outdoors on the rooftop of the University of Dodoma, located at 6.5738° S and 36.2631° E in Tanzania, were used to record the power output during the winter season. The average data of ambient temperature, module temperature, solar irradiance, relative humidity, and wind speed recorded is used to predict the power output using a non-linear autoregressive artificial neural network. We consider the Levenberg-Marquardt optimization, Bayesian regularization, resilient propagation, and scaled conjugate gradient algorithms to understand their abilities in training, testing and validating the data. A comparison with reference to the performance indices: coefficient of determination, root mean square error, mean absolute percentage error, and mean absolute bias error is drawn for both modules. According to the findings of our investigation, the predicted results are in good agreement with the experimental results. All the algorithms performed better, and the predicted power out of both modules using the Bayesian regularization algorithm is observed to exhibit good processing capabilities compared to the other three algorithms that are evident from the measured performance indices.

Metallurgical infrastructure and technology criticality: the link between photovoltaics, sustainability, and the metals industry

Various high-purity metals endow renewable energy technologies with specific functionalities. These become heavily intertwined in products, complicating end-of-life treatment. To counteract downcycling and resource depletion, maximising both quantities and qualities of materials recovered during production and recycling processes should be prioritised in the pursuit of sustainable circular economy. To do this well requires metallurgical infrastructure systems that maximise resource efficiency.To illustrate the concept, digital twins of two photovoltaic (PV) module technologies were created using process simulation. The models comprise integrated metallurgical systems that produce, among others, cadmium, tellurium, zinc, copper, and silicon, all of which are required for PV modules. System-wide resource efficiency, environmental impacts, and technoeconomic performance were assessed using exergy analysis, life cycle assessment, and cost models, respectively. High-detail simulation of complete life cycles allows for the system-wide effects of various production, recycling, and residue exchange scenarios to be evaluated to maximise overall sustainability and simplify the distribution of impacts in multiple-output production systems. This paper expands on previous studies and demonstrates the key importance of metallurgy in achieving Circular Economy, not only by means of reactors, but via systems and complete supply chains—not only the criticality of elements, but also the criticality of available metallurgical processing and other infrastructure in the supply chain should be addressed. The important role of energy grid compositions, and the resulting location-based variations in supply chain footprints, in maximising energy output per unit of embodied carbon footprint for complete systems is highlighted.

Dynamic and Static Reconfiguration Analysis of Solar PV Array

Solar photovoltaic (PV) systems are increasingly attractive due to renewable in nature. Solar PV module technologies are paying more attention to enhance the energy production. Partial Shading (PS) will reduce the output power of the PV panel. The PS also causes problems such as mismatch loss and hotspots. This work proposes an analysis of the PS of Total Cross Tied (TCT), SuDoKu and Dynamic Reconfiguration of PV array with 3 × 3 PV modules. The proposed work will extract the maximum power extraction in dynamic reconfiguration under partial shading condition. The comparative investigation was presented for six shading patterns in the terms of Percentage Power Loss (PLL) and Fill Factor (FF). The percentage power loss and mismatch loss obtained in TCT and SuDoKu is 39.8% and 41.7% which is drastically reduced in dynamic reconfiguration is 33.2% and 23.64% respectively.

Energy Efficiency of Multi-Technology PV Modules under Real Outdoor Conditions—An Experimental Assessment in Ghardaïa, Algeria

Energy efficiency and ratio performance are two key parameters for the analysis of the performance of photovoltaic (PV) modules. The present paper focusses on the assessment of the efficiency of four different photovoltaic module technologies based on energy efficiency and ratio performance. These PV modules were installed at the Applied Research Unit in Renewable Energy (URAER) in Algeria and were used to provide experimental data to help local and international economical actors with performance enhancement and optimal choice of different technologies subject to arid outdoor conditions. The modules studied in this paper are: two thin-film modules of copper indium selenide (CIS), hetero-junction with intrinsic thin-layer silicon (HIT) and two crystalline silicon modules (polycrystalline (poly-Si), monocrystalline (mono-Si)). These technologies were initially characterized using a DC regulator based on their measured I-V characteristics under the same outdoor climate conditions as the location where the monitoring of the electrical energy produced from each PV module was carried out. The DC regulator allows for extracting the maximum electrical power. At the same time, the measurements of the solar radiation and temperature were obtained from a pyranometer type Kipp & ZonenTM CMP21 and a Pt-100 temperature sensor (Kipp & Zonen, Delft, Netherlands). These measurements were performed from July 2020 to June 2021. In this work, the monthly average performance parameters such as energy efficiency are given and analyzed. The average efficiency of the modules over 12 months was evaluated at 4.74%, 7.65%, 9.13% and 10.27% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The calculated percentage deviations in the efficiency of the modules were 8.49%, 18.88%, 19.74% and 23.57% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The low variation in the efficiency of the HIT module can be attributed to the better operation of this module under arid outdoor conditions, which makes it a promising module for adaptation to the region concerned.

Characterisation of degradation of photovoltaic (PV) module technologies in different climatic zones in Ghana

Degradation of photovoltaic (PV) modules depends on technology and environmental conditions. This study characterised the degradation rates of different PV module technologies in three climatic zones in Ghana to determine the technology that would suffice specific environmental conditions in Ghana. The study sampled 104 PV modules of different technologies and ages from 16 PV systems in these climatic zones. The study employed current–voltage (I-V) curve tracing for data collection. The results revealed that the median power degradation rates of monocrystalline silicon modules were least with 0.76%/year and 1.39%/year in Dry Equatorial Climatic Zone and Interior Savannah Climatic Zone respectively, followed by polycrystalline silicon modules with 1.31%/year, 1.35%/year and 1.57%/year in Dry Equatorial Climatic Zone, Wet Semi Equatorial Climatic Zone and Interior Savannah Climatic Zone respectively and highest in amorphous silicon modules with 1.62%/year and 1.67%/year in Dry Equatorial Climatic Zone and Interior Savannah Climatic Zone respectively. The same module technology degraded differently within the same climatic zone, and from one climatic zone to another. Module degradation rates also varied from one location to another. However, crystalline silicon modules performed creditably in all the climatic zones and thus, could suffice better in these climatic zones in Ghana than amorphous silicon modules.