Performance Of Solar Modules Research Articles

Enhancing Conductivity of Nickel Oxide to Achieve Scalable Preparation for High-Efficiency Perovskite Solar Modules

NiOx, prepared via the sputtering method, exhibits low conductivity and energy level mismatch with the perovskite layer, thereby limiting further enhancements in the performance of perovskite solar modules (PSMs). Unlike traditional methods that enhance the performance of NiOx through reactive sputtering or directly doping NiOx targets with metal ions, both of which incur high costs and low efficiency, we employ an evaporation method using LiF to achieve efficient and low-cost doping of NiOx. Compared to the pristine NiOx, the incorporation of LiF significantly increases the conductivity of NiOx. Additionally, the incorporation of LiF enhances the quality of the deposited perovskite films, as well as the energy level alignment and symmetry between NiOx and the perovskite, effectively improving the hole extraction and transport capabilities between NiOx and the perovskite. As a result, the PSM (active area of 57.30 cm²) fabricated in air achieves an impressive efficiency of 19.54%. Furthermore, the unencapsulated PSM retains 80% of its initial efficiency after 700 h of continuous illumination, whereas the NiOx-based PSM drops to 80% after only 150 h. This study provides a simple and low-cost method for doping NiOx, which is of great significance for the further industrialization of PSMs.

Bending deformation effects on the optoelectronic performance of flexible GaInP/GaAs/InGaAs triple junction solar cells

To achieve genuine carbon neutrality, PV-powered vehicles show promise for future automotive development. However, the impact of curved surfaces on flexible solar cell module performance remains uncertain. This study specifically focuses on newly-designed flexible GaInP/GaAs/InGaAs triple junction solar cells, which have the highest potential output efficiency. A computational model was developed to analyze the electrical performance of curved solar cells, and variations in short-circuit current (Isc) and open-circuit voltage (Voc) with bending angles were determined to closely match experimental data. The effects of incident light intensity, angle, and bending strain on solar cell performance were analyzed to explain the observed Isc and Voc trends. This method can be applied to other III-V group solar cells, providing theoretical support for accurately calculating the performance of curved solar cell modules.

Reliable Prediction of Solar Photovoltaic Power and Module Efficiency using Bayesian Surrogate Assisted Explainable Data-Driven Model

This study proposes a Bayesian surrogate-driven explainable deep neural network model to predict and interpret the module efficiency and maximum output power of three commercially available photovoltaic modules: monocrystalline silicon, polycrystalline silicon, and amorphous silicon during the winter season. In addition, the influence of the photovoltaic material and ambient conditions on the predicted power and module efficiency is investigated. The model inputs include solar irradiance, module material (monocrystalline, polycrystalline, and amorphous silicon), season of the year (months), and time of day (morning to evening). Experiments were conducted on these three modules during the winter using data from Rawalpindi, Pakistan. These data were then fed into the deep neural network model to train and yield predictions. Several preprocessing techniques such as logarithmic transformation, square root, cube root, reciprocal, and exponential transformations are employed to improve the linearity of distributed data. For hyper-parameters optimization, Gaussian process, gradient boost regression trees, and random forest are used. The results show that the optimal deep neural network using random forest surrogate model along with square root and exponential transformation is able to predict the maximum power output and module efficiency of the considered photovoltaic modules for the entire investigated period with a correlation coefficient, R2 = 0.998. The least accurate model (R2=0.991) is a Gaussian process using simple data distribution. These results hold valuable insights for predicting and optimizing the performance of other solar photovoltaic modules in various climates and different seasons of the year.

Bilayer interface engineering through 2D/3D perovskite and surface dipole for inverted perovskite solar modules

The persistency of passivation and scalable uniformity are vital issues that limit the improvement of performance and stability of large-area perovskite solar modules (PSMs). Here, we design a bilayer interface engineering strategy that takes advantage of the stability and passivation ability of low-dimensional perovskite and the dipole layer. Introducing phenethylammonium iodide (PEAI) can form 2D/3D heterojunctions on the perovskite surface and effectively passivate defects of perovskite film. Interestingly, the upper piperazinium iodide (PI) layer can still form surface dipoles on the 2D/3D perovskite surface to optimize energy-level alignment. Moreover, the bilayer interface engineering enables large-area perovskite films with uniform surface morphology, lower trap-state density and stability against environmental stress factors. The final devices achieved a small-area PCE of 25.20% and a large-area (1 cm2) PCE of 23.96%. A perovskite mini-module (5 × 5 cm2 with an active area of 14.28 cm2) could also be fabricated to achieve a PCE of 23.19%, ranking it among the highest for inverted PSMs. Additionally, the device could retain over 93% of its initial efficiency after MPP tracking at 45 °C for 1280 hours. This study successfully demonstrates a bilayer interface engineering with respective functions, offering valuable insights for producing efficient and stable large-area PSCs.

Monitoring solar irradiance and PV module performance in mobile applications

The paper presents a comprehensive evaluation of a PV module attached to an electric vehicle using a custom developed PV monitoring system to estimate the effect of PV energy production on the driving range.A rigid crystalline silicon photovoltaic (PV) module with a nominal peak power of 192.4 W accompanied with four irradiance sensors (positioned horizontally and vertically to the left, right and back) was mounted on an electric car, and various driving scenarios were executed, with data recorded for analysis. The results of a two-month continuous monitoring of the car's usage mainly in the Central Slovenia region in late winter and early springtime, show that the daily energy generation by the installed PV module contributed an additional driving range of up to 5 km per day, totalling 93 km of additional range in the entire monitoring period. Based on irradiance monitoring results applied to a hypothetical case where all sides would be covered with a state-of-the-art PV, the driving range would extent to 471 km in total for the same period. When compared to a fixed, ideally installed PV module at our outdoor PV monitoring site in Ljubljana, the average performance ratio (PR) of the mobile PV module in the two-month period was 87 %, whereas the PR of the fixed installed PV module was 83 %. The energy yield varied significantly under the varying conditions resulting from different car usage scenarios and on average it reached 41 % of the fixed PV module's energy yield. Through real-world experiments and data collection, different car use cases under various driving and parking conditions are presented and evaluated in detail. From these, the base specifications of a dedicated mobile VIPV monitoring system are identified.

Anomalous Electroluminescence Characteristics of Perovskite Modules.

Spatially resolved photoluminescence (PL) and electroluminescence (EL) imaging technologies play a crucial role in evaluating the performance and stability of photovoltaic devices. However, their application in perovskite devices presents unique challenges. In this study, we report a discrepancy between the electrical performance of perovskite solar modules (PSMs) and the EL images. Following the application of a reverse bias voltage, we observed an increase in EL brightness associated with prolonged carrier lifetime and transport length. Furthermore, cross-sectional Kelvin probe force microscopy identified a significant potential increase primarily at the electron-transport layer (ETL) side after reverse bias, suggesting the presence of defective ETL/perovskite interfaces with filled hole traps. To address this EL mismatch, we proposed a mild reverse current recovery method aimed at aligning EL images with the cell performance without compromising device efficiency. This approach effectively mitigates discrepancies, ensuring alignment between the device performance and EL imaging. Our study underscores that caution is required when utilizing EL imaging to monitor spatial homogeneity in PSMs for future industrial production.

Influence of vortex generator on performance of concentrated solar photovoltaic module in existence of heat sink

New configuration of concentrated photovoltaic thermal (CPVT) with the implementation of parabolic concentrator and heat sink combined with the vortex generator (VG) were presented in current work. The testing fluid is water and temperature-dependent features were utilized. The regime of water flow in absence and presence of VG are laminar and turbulent, respectively. Numerical simulations were done for different values of angle of VG (θ = 30°, and 60°), pitch ratio (S = 0.025, 0.0375, and 0.05), and volumetric flow rate (Q = 0.5, to 2 Lit/min). Four values for width of reflector have been applied and radiation model was utilized to derive the absorbed heat flux. The accuracy of modeling has been examined for three cases and good accommodations have been reported. The maximum values of thermal (ηth) and electrical (ηel) performance are 63.75 % and 13.96 % which happens when θ = 30°, S = 0.025, Q = 2 Lit/min. Installing VG leads to increments of ηth and ηel about 1.42 % and 2.74 %. Increase of S and θ cause performance to decrease while this function increases with rise of Q. Increase of Q causes ηth and ηel to increase about 1.17 % and 2.55 % for the best case.

The impact of some environmental variables on the performance of solar PV module

The country of Iraq tops the list of countries in solar activity and therefore has the most important renewable energy sources, which we desperately need to fill the acute shortage of electrical energy. The availability of this source coincides with a significant rise in temperature in most of its regions and a wide range of days of the year. Where temperatures play a key role in wind activity and the provocation of dust storms, which urgently requires a field study to find out the impact of these factors on the performance of photovoltaic solar modules. Therefore, this study aimed to evaluate the performance of the solar module under the influence of dust accumulation, temperature and wind speed. A group symmetric of monocrystalline silicon solar modules have been experimented to see how these factors affect the performance of the modules. The results showed that there is a clear impact by the heat factor and dust accumulation on the performance of solar modules, but the wind factor is the least influential and what can be concluded is that Iraq, especially the city of Baghdad, is an ideal place to invest solar energy in the production of electrical energy.

Detecting the faults of solar photovoltaic module due to the temperature and shading effect by convolutional neural network

This study aims to use the convolutional neural network (CNN) to build a new model for detecting the faults of solar PV module performance under the temperature and shading effects. Two sets of data were used based on solar data from Mendeley, and experimental data from the University of Sharjah. The transfer learning model was also used in this study. Both CNN and transfer learning models were trained and tested for Mendeley and experimental data under different data and epoch numbers. The accuracy of both models was tested under different numbers of data and epochs. The accuracy was higher than 96 % for 50 epochs when half and full data were used for both models. In comparison, the transfer learning model still shows 90 % for all data when the number of epochs is reduced to 10 epochs. The transfer learning model in this study can be used to detect faults in other renewable energy applications, such as wind energy systems.

Full-spectrum radiative cooling for enhanced thermal and electrical performance of bifacial solar photovoltaic modules: A nationwide quantitative analysis

Bifacial photovoltaic (bPV) technologies have been garnering increasing attention in recent years due to their ability to generate more power than conventional PV systems. Passive radiative cooling through spectrally selective absorption/emission is considered one of the most practical and cost-effective solutions for the thermal management of bPV modules. In this study, a full-spectrum radiative cooling (FRC) strategy was proposed to maximize the thermal and electrical performance of bPV modules by enhancing above-bandgap absorption, sub-bandgap reflection, and thermal radiation. A multi-physics model was established to characterize bPV performance, enabling analysis of the module's spectral and thermal responses to full-spectrum light under dynamic weather conditions. The proposed model was validated through outdoor experiments with a commercial bPV module, demonstrating good prediction accuracy. To quantify the radiative cooling effect of the ideal FRC strategy and compare it with the ideal traditional radiative cooling (TRC) strategy, a nationwide simulation analysis was conducted across 32 cities in China. The results indicate that the ideal FRC strategy can achieve an annual average temperature reduction of 2.3–4.4 °C and an additional power gain of 7.3%–8.4% for commercial bPV modules. In comparison, the ideal TRC strategy can only achieve an annual average temperature reduction of 1.1–2.2 °C and an additional power gain of 0.38%–0.89%. Results from correlation analysis and sensitivity analysis show that among environmental parameters, wind speed has the most significant positive effect on lowering module temperature, while precipitable water vapor has a relatively small negative impact. Overall, this research demonstrates that the FRC strategy holds great potential for reducing temperature and boosting power output in PV devices, paving the way for promoting the development of sustainable and efficient PV systems.

Ultrasonic C-scan for micro-crack inspection on semi-flexible solar modules

Solar photovoltaic modules are versatile power sources in diverse materials and configurations, including compact and flexible variants for portable electronic devices. Ensuring the reliability of these modules is crucial for sustaining the functionality of the devices they power. Manufacturing or handling-induced defects, such as cracks or scratches, pose a threat to the performance of solar modules. Hence, non-destructive inspection becomes essential in the quality control process. Ultrasonic C-scan has been an established inspection technique within various industries; however, its application on solar modules remains uncommon. On the other hand, Scanning Acoustic Microscopy (SAM) has been implemented for observing defects in solar cells, yet employing SAM for comprehensive module scanning is inefficient. This study aims to assess the capability of ultrasonic c-scan in detecting micro-cracks within semi-flexible solar panels and to evaluate the effects of frequency selection on the results. This work investigates the specimen with an Ultrasonic C-Scanner at different frequencies. Subsequently, the outcomes are validated by comparing them with the results from the SAM. The potential of using a widely known ultrasonic technique for this purpose, while understanding its limitations, such as the c-scan, will enable a more straightforward integration of the technique into the solar module quality control process.

Impact of additive manufacturing materials on thermal performance of silicon reference cells

Additive manufacturing, or 3D printing, is quickly becoming a widespread manufacturing method offering timely and cost-effective build times for unique part geometries with an increasing range of material offerings. One unique use for additive manufacturing is constructing the housing for reference solar cells, which are crucial instruments for evaluating the electrical performance of photovoltaic solar cells and modules. These instruments, which require good thermal conduction, are costly to manufacture because they are usually machined from aluminum using precision milling machines. In this work, we set out to evaluate several presently available additive manufacturing materials for their thermal properties when used to house reference solar cells. We fabricated several types of reference cell instruments with a tabletop, filament-based 3D printer using polylactic acid (PLA) and composite PLA/metal materials with different infill percentages. Furthermore, we fabricated several all-metal 3D printed reference cells using a binder jet printed stainless steel-bronze material blend and compared the thermal properties of all 3D printed instruments against a standard aluminum housing reference cell. Measurements included temperature monitoring of an embedded thermocouple sensor on an isothermal plate under the ambient environment and when exposed to high irradiation under a solar simulator. Current vs voltage measurements were also taken under the solar simulator and the open circuit voltage results were used to verify the actual silicon cell temperature. Our findings indicate that the stainless steel-bronze option can function well as an alternative to traditional aluminum-based housings, while the lower-cost metal-PLA composite can only be used under indoor light spectra or when used in a flash-type solar simulator when the instrument is not exposed to excessive radiation and heat.

Modeling and Simulation of Solar Irradiance Conversion Using the Pyranometer App

Solar irradiance is the amount of light energy that the sun emits and reaches the earth. The Pyranometer app is used to gather sample data. This predictive model calculated the electricity a solar module generates based on solar irradiance. It can calculate the voltage, current, and power a solar module can produce from solar irradiance. The study used a developmental-evaluative design using simulation modeling created using Matlab® and Simulink®. The evaluation of the model's accuracy was confirmed on a parallel run with an existing renewable solar energy facility to assess functionality, performance, robustness, workmanship, and the overall recommendation of the model. Findings revealed promising results that the designed model could, with reliable accuracy, simulate a solar module's performance from a given amount of irradiance.

Boosting the energy output of an On-Grid solar PV system using a novel techniques

Two techniques have been used in this study to boost energy output of an on-grid PV system. Boosting energy output is achieved by educating the PV solar system performance parameters. Planar concentrators and cooling are two techniques used to boost energy output. The current solar PV system is placed in Baghdad/Al-Taji. This work includes improving the following performance parameters: performance ratio (PR), array efficiency, array yield, electrical energy, as well as solar irradiation. All of these improvements are accomplished by improving solar irradiance using planar concentrators (made of aluminum metal) and cooling (via water). The monthly daily average of energy produced for enhanced and reference PV modules is 14.2 kWh and 11.1 kWh, respectively. The monthly daily average of the array yield to the enhanced PV modules and reference PV modules is 7.14 kWh/kWp and 5.61 kWh/kWp, respectively. The monthly daily average of solar irradiation to the enhanced and reference PV modules is 7.71kWh/m2 and 6.101kWh/m2, respectively. The monthly daily average efficiency and performance ratio of the enhanced and reference PV modules are 14.3% & 93.6%, and 13.9% & 91.1%, respectively. The maximum average monthly temperatures of the enhanced and reference PV modules are in July, at 48.5OC and 57.4OC respectively, where the ambient air temperature is 42.1OC. The novel aspect of this work is the successful optimization of the performance (PR) parameters of an on-grid PV system using the new equations. Besides from designing a novel system to improve the performance of solar PV modules of the second generation (CIGS).

Evaluation of the Performance of Polycrystalline and Monocrystalline PV Technologies in a Hot and Arid Region: An Experimental Analysis

In arid regions, the behavior of solar panels changes significantly compared to the datasheets provided by the manufacturer. Therefore, the objective of this study is to determine the performance of both polycrystalline and monocrystalline solar modules in an arid region characterized by a large potential for solar irradiation and high temperatures. The influence of environmental parameters, such as temperature and dust, on the output power of solar modules with different technologies (monocrystalline and polycrystalline) has been investigated. The Artificial Hummingbirds Algorithm (AHA) has been used to extract parameters for PV modules. As a result, it has been demonstrated that for high solar irradiation, the polycrystalline PV module experiences a smaller decrease in output power than the monocrystalline PV module as the module temperature increases. The percentage drop in output power is approximately 14% for the polycrystalline PV module and nearly 16% for the monocrystalline PV module. However, for low solar irradiation, it is advisable to use monocrystalline modules, as a 21% decrease in power was observed for polycrystalline modules compared to a 9% decrease for monocrystalline modules. Additionally, the monocrystalline PV module was more affected by dust than the polycrystalline PV module under high solar irradiation conditions, while under low incident solar radiation, the polycrystalline PV module was more affected by dust than the monocrystalline PV module. The power drop of the monocrystalline PV module was greater than that of the polycrystalline PV module for high solar radiation (>500 W/m2). Therefore, the advantage of this proposed work is to recommend the use of polycrystalline solar panels in regions characterized by high solar irradiation and high temperatures instead of monocrystalline solar panels, which are more efficient in regions worldwide characterized by low solar irradiation and low temperatures.

Simulation of left-handed materials for GaAs solar cells

The optical performance of photovoltaic solar cells and modules is affected by the significant reflection losses at the air/glass front interface. Several antireflection coating materials on solar glass are introduced to overcome this drawback as a mechanism for light trapping. We propose in this study a novel structure containing silicon nitride (SiNx), left-handed materials (LHMs), and the light absorbing material (gallium arsenide, GaAs), to minimize the reflection and increase the light absorption. The transfer matrix method was used to compute the reflectivity and absorption of both normal and transverse magnetic polarized light. The results show that left-handed materials have an available good impact on the efficiency of solar cells by increasing the light absorption through the proposed structure where the absorbance achieves values greater than 80% in the entire light spectrum.

The Performance of Polycrystalline and Monocrystalline Solar Modules Under The Climate Conditions of El-Kharga Oasis, New Valley Governorate, Egypt

The Performance of Polycrystalline and Monocrystalline Solar Modules Under The Climate Conditions of El-Kharga Oasis, New Valley Governorate, Egypt

The Effects of Non-Uniformly-Aged Photovoltaic Array on Mismatch Power Loss: A Practical Investigation towards Novel Hybrid Array Configurations

One of the most important causes of a reduction in power generation in PV panels is the non-uniform aging of photovoltaic (PV) modules. The increase in the current–voltage (I–V) mismatch among the array modules is the primary cause of this kind of degradation. There have been several array configurations investigated over the years to reduce mismatch power loss (MPL) caused by shadowing, but there have not been any experimental studies that have specifically examined the impact of various hybrid array topologies taking PV module aging into consideration. This research examines the influence of the non-uniform aging scenario on the performance of solar PV modules with various interconnection strategies. Experiments have been carried out on a 4 × 10, 400 W array with 12 possible configurations, including three proposed configurations (LD-TCT, SP-LD, and LD-SP), to detect the electrical characteristics of a PV system. Finally, the performances of different module configurations are analyzed where the newly proposed configurations (SP-LD and LD-SP) show 15.80% and 15.94% higher recoverable energy (RE), respectively, than the most-adopted configuration (SP). Moreover, among the twelve configurations, the SP configuration shows the highest percentage of MPL, which is about 17.96%, whereas LD-SP shows the lowest MPL at about 4.88%.

Dithiols enhance the photovoltaic performance and stability of perovskite solar cells and modules by elongating the carrier lifetime

Metal-halide perovskite solar cells (PSCs) exhibit outstanding efficiencies when fabricated as mm-sized cells, but the fabrication of high-performing larger-area modules presents a challenge. Emerging evidence suggests the serious recombination reaction caused by the limited carrier lifetime is the bottleneck, because we lack effective strategy to deposit large-area perovskite film with sufficient long carrier lifetime. Herein, we report on a strategy of modulating the formation of perovskite film on larger-area substrates via introducing alkyl dithiol additives. Among the dithiols with different lengths, we find hexane-1,6-dithiol can effectively elongate carrier lifetime of perovskite film from 1.5 to 7.6 μs, which is due to the suppression of the formation of inactive PbI2 and hexagonal δH phase, along with the enlarged grain size. As a result, we improved the efficiency of solar cells (0.16 cm2) from 21.8% to 23.5%, as well as 16.9%–18.1% for the mini-modules (10.0 cm2). More importantly, the modified modules retained 92% of their initial efficiencies after 500-h aging under ambient condition without encapsulation (ISOS-D-1). This dithiol additive strategy shows great promise for pursuing high-performance PSCs.

Parametric study of design factors on the performance of flexible solar modules

ABSTRACT Solar cells have traditionally been built on rigid substrates. However, a lot of research is currently going on to improve the design and performance of solar cells built on flexible substrates. Flexible solar cells are light and rugged; however, the cell’s efficiency is highly affected by factors related to the design or the environment. In many instances, the effect of one factor on the performance of solar modules is affected by the levels of other factors. Therefore, in this work, analysis of variance (ANOVA) tools were used to study the simultaneous effect of design factors of shading, air gap, and curvature on the performance of flexible solar modules. Furthermore, an artificial neural network used the experimental data to predict the performance of the modules under similar conditions. The ANOVA results showed that all the main factors were significant and directly influenced the performance of the solar module. Furthermore, the combined effect of the factors is also significant. Furthermore, the ANN model was able to predict the performance of the modules with high precision, as indicated by the coefficient of determination (R2) value of 99.92%.