Monocrystalline Photovoltaic Modules Research Articles

Comparative experimental analysis of monocrystalline and polycrystalline photovoltaic panel through hybrid phase change material

Photovoltaics thermal management is utmost necessary as continuous heating of the module decreases the performance. This paper presents a comparative study in terms of performance of two photovoltaic modules namely monocrystalline and polycrystalline using hybrid phase change materials (PCMs). The hybrid PCMs of RT31 and RT 44HC were prepared by method of stirring. The final prepared hybrid PCMs were poured at the back of panel and panel was covered. The purpose of these experiments is to improve the efficiency of polycrystalline and monocrystalline photovoltaic modules and comparing which technology is more efficient having hybrid PCM. The experiments were performed under the room conditions in Taxila, Pakistan. The output parameters of the photovoltaic module appeared to be strongly dependent upon the solar irradiance. The power output and efficiency of monocrystalline and polycrystalline photovoltaic module were measured. The monocrystalline panel maximum temperature was 36.59 °C as compared to polycrystalline panel which was 40.23 °C. As the radiation intensity increased till noon, electrical power was improved, and it was 6.52 W in monocrystalline panel as compared to polycrystalline panel which was 6.32 W. Electrical conversion efficiency was also observed, and it was maximum up to 11.84 % in monocrystalline panel. The higher performance was observed in case of monocrystalline panel having hybrid in terms of performance as compared to polycrystalline panel.

Analysis of Dust Properties and Deposition Loss in Mono and Poly Crystalline Photovoltaic Modules in Southern Rajasthan

Analysis of Dust Properties and Deposition Loss in Mono and Poly Crystalline Photovoltaic Modules in Southern Rajasthan

The Study of Partial Shading on Mono and Poly Crystalline Photovoltaic Modules in Southern Rajasthan

The Study of Partial Shading on Mono and Poly Crystalline Photovoltaic Modules in Southern Rajasthan

Long-Term Energy Yield Analysis of the Rooftop PV System in Climate Conditions of Poland

In the past four years, the number of prosumers utilizing photovoltaic (PV) installations in Poland has increased significantly, exceeding 1.3 million, reaching a total power capacity of 10.5 GW by the end of 2023. This paper presents a three-year energy yield analysis of the prosumer PV systems operating in Eastern Poland. The 9.6 kW system consists of high-efficiency monocrystalline photovoltaic modules in half-cut technology. Over the three years of operation, specific yields have been analyzed along with weather parameters, such as solar intensity, outdoor temperature, humidity, wind speed, rainfall, or snowfall. The average annual final yield was found to be relatively high, exceeding 1000 kWh·kW−1 in each of the analysed years. The highest monthly specific yields of the analysed period were noticed during the summer, reaching the maximum value of 164 kWh·kW−1 in 2022. The daily final yields varied from a minimum of 0.15 kWh·kW−1 in Winter 2021 to a maximum of 6.8 kWh·kW−1 in Spring 2022. Weather conditions increasing the energy yields, such as low average ambient temperatures together with high insolation periods, were noticed. Energy production in such favorable conditions reached a surprisingly high value of energy yield in April 2020, comparable to the summer months (151.0 kWh·kW−1). The occurrence of heavy rainfall in summer was also noted as a desirable effect that leads to the natural cleaning of the PV modules. The average performance ratio during the analyzed period was found to be 0.85. The energy production of the PV system allowed the reduction of about 21 tons of CO2 emission.

An efficient, fast, and robust algorithm for single diode model parameters estimation of photovoltaic solar cells

AbstractParameter estimation of photovoltaic (PV) solar cells and module models pays attention to researchers owing to their importance in practical considerations. The single diode model (SDM) circuit with five unknown parameters is widely used to model PV solar cells and modules. In this paper, a novel approach called alternate optimization (AO) algorithm based on a discrete search is proposed to estimate the SDM parameters. The proposed algorithm provides efficient and robust performance, considering a limited set of discrete values and increasing the convergence speed. Two practical case studies with actual measurements are considered to assess the proposed AO algorithm: the RTC France solar cell and monocrystalline PV modules with different irradiations and temperatures. The numerical findings underscore the superior performance of the proposed AO algorithm across various metrics. Notably, it achieves an exceptional Root Mean Square Error (RMSE) of 7.7426 × 10−04 for the RTC France PV cell and approximately 1 × 10−03 RMSE for monocrystalline PV modules. Additionally, the algorithm exhibits unparalleled speed, showcasing the fastest convergence with an elapsed time of 1.66 × 10−05—markedly 4.45 times quicker than the fastest method documented in the literature for SDM parameter estimation. Furthermore, the proposed AO algorithm stands out for its efficiency, requiring a maximum of five iterations for parameter estimation, a substantial improvement compared to the more than 10 iterations typically needed by algorithms in the existing literature. Its robustness is also commendable, as evidenced by the stability of final RMSE values across a variety of experiments, distinguishing it from less robust algorithms found in the literature.

Mechanical integrity of photovoltaic panels under hailstorms: Mono vs. poly-crystalline comparison

The performance of Photovoltaic (PV) modules heavily relies on their structural strength, manufacturing methods, and materials. Damage induced during their lifecycle leads to degradation, reduced power generation and efficiency. Mechanical stresses, originating from manufacturing, transportation, and operational phases impose significant loads on PV modules. These in-service loads encompass various environmental forces such as wind, snow, dust, hail, rain, and heat. In-service loads encompass static and dynamic forces such as wind, snow, dust, hail, rain, and heat. Among these factors, the mechanical loads from hail impacts play a crucial role in PV module performance and require a comprehensive investigation. This research focuses on evaluating the impact of hail loads on different PV modules, following international standards like ASTM 1038-10 and IEC-61215-2. The developed simulator effectively assesses the reliability of PV modules. The number of busbars within a PV module was identified as a key factor influencing the module's resilience to hail impacts. Notably, mono-crystalline PV modules exhibited better resistance to hail loads compared to their poly-crystalline counterparts. The PV modules experience micro-cracking due to hail impacts, leading to an efficiency reduction of 4.15% in mono-crystalline modules and 12.59% in poly-crystalline modules. Similarly, the generated power output decreased by 3.3% and 12.5%, respectively, in these module types.

Electrical Characteristics of Half-Cut Bifacial PERC Monocrystalline Photovoltaic Modules under Outdoor Conditions in Nawabshah

Electrical Characteristics of Half-Cut Bifacial PERC Monocrystalline Photovoltaic Modules under Outdoor Conditions in Nawabshah

Use an artificial intelligence method (Machine Learning) for analysis of the performance of photovoltaic systems

The performance of a photovoltaic system depends on several parameters such as temperature, clouds, and the season, which makes the study of PV performance from monitoring databases very complex given the size of the information and the complexity of the phenomena involved. This article applies an artificial intelligence (AI) method based on machine learning (ML). For more efficient analysis, the Support Vector Machine (SVM) is used to simplify and optimize the processing of these data for the study of the performance of PV systems. More precisely, we group a multi-class data variable according to the needs of the analysis using SVMs. In this article, we present all the stages of data processing based on the application of artificial intelligence (AI). We present as an example the results obtained in the study of the performance of a 150W monocrystalline photovoltaic (PV) module after one year of monitoring.

Degradation and energy performance evaluation of mono-crystalline photovoltaic modules in Egypt

Degradation reduces the capability of solar photovoltaic (PV) production over time. Studies on PV module degradation are typically based on time-consuming and labor-intensive accelerated or field experiments. Understanding the modes and methodologies of degradation is critical to certifying PV module lifetimes of 25 years. Both technological and environmental conditions affect the PV module degradation rate. This paper investigates the degradation of 24 mono-crystalline silicon PV modules mounted on the rooftop of Egypt's electronics research institute (ERI) after 25 years of outdoor operation. Degradation rates were determined using the module's performance ratio, temperature losses, and energy yield. Visual inspection, I–V characteristic measurement, and degradation rate have all been calculated as part of the PV evaluation process. The results demonstrate that the modules' maximum power ({P}_{max}) has decreased in an average manner by 23.3% over time. The degradation rates of short-circuit current ({I}_{sc}) and maximum current ({I}_{m}) are 12.16% and 7.2%, respectively. The open-circuit voltage ({V}_{oc}), maximum voltage ({V}_{m}), and fill factor (FF) degradation rates are 2.28%, 12.16%, and 15.3%, respectively. The overall performance ratio obtained for the PV system is 85.9%. After a long time of operation in outdoor conditions, the single diode model's five parameters are used for parameter identification of each module to study the effect of aging on PV module performance.

Effects of wind speed and temperature on economics and environmental impact assessment of different solar PV systems in Malaysia

This study aims to analyse the effect of temperature and wind speed on the performance of different types of photovoltaic (PV) systems at a different state in Malaysia and how it affects the economics and environmental impact assessment in the present year of 2018 as well as future years in 2030 and 2040. Three types of grid-connected solar PV modules namely Mono-Crystalline, Poly-crystalline, and Thin Film were selected to be implemented in different cities of Shah Alam, Chuping, Alor Setar, Ipoh and Kota Kinabalu. A mathematical model was adopted to estimate the performance characteristics of the solar PV modules. Based on the data in the present year, the highest power output produced by the Mc-Si module for Alor Setar city is given by 33.40 MWh/year while the lowest amount of power output provided by this PV panel is about 28.18 MWh/year in Shah Alam. Furthermore, an area of 144 m2 for the Mono-Crystalline PV module can satisfy the total energy requirement by the resident as it was the most profitable to be implemented compared to Poly-crystalline and Thin Film. The findings of this study can serve as important information on the economic viability of installing PV systems in the selected cities in Malaysia.

Experiment and model of a photovoltaic module with evaporative cooling

Most studies on evaporative cooling of photovoltaic modules have primarily relied on experimental investigations without any general model to investigate the module performance. In this paper, an experimental model similar to that of solar collector performance was developed in terms of total efficiency and ratio of temperature difference between cooling fluid and ambient temperatures with solar radiation for finding the module thermal characteristics which were optical efficiency and module overall heat loss coefficient, the module temperature, and then the generated electrical power. To validate the model, experimental tests were conducted on a 320 Wp monocrystalline photovoltaic module of 1.956 m × 0.992 m area equipped with an evaporating surface at the module rear surface on some clear sky and cloudy days in Chiang Mai, Thailand. The evaporating pad was made of cellulose and polypropylene with 5 mm thickness. A controlled flow rate of water at 0.3 L/min was maintained with inlet temperatures ranging between 25 and 35 °C, ensuring a non-dripping condition. The results from the new simplified model demonstrated good agreement with the experimental data. In addition, the developed model was also used to predict the yearly performance of the photovoltaic module with evaporative cooling under tropical climate of Chiang Mai. The average total and net monthly electrical output were increased 7.04 and 4.47%, respectively compared to that of the normal unit. In case of hot and arid area such as Ouargla, Algeria, better improvement of PV module performance could be attained, and the average total and net monthly power generation could be enhanced 8.62 and 6.48%, respectively.

Parameter extraction of photovoltaic module model by using Levenberg-Marquardt algorithm based on simulated annealing method

Reliable and accurate parameter identification of solar modules model is necessary to evaluate the performances and to control the behavior of photovoltaic systems. In this work, Levenberg-Marquardt combined with simulated annealing algorithm is proposed to extract the five parameters from the experimental data points ( $$I_\text {{PV}}$$ - $$V_\text {{PV}}$$ ) of Photowatt-PWP 201 polycrystalline module. The quality evaluation of the obtained outcomes is ensured by the analysis of the objective function accuracy. Therefore, the proposed method provides the highest precision compared to the results of the most recent methods reported in the literature. Moreover, a study of the convergence process has been established in the aim to observe the adjustment way of the five parameters and to assess the influence of the damping factor on the objective function optimization. The superiority of the proposed method in terms of accuracy have been tested and proven by using the $$I_\text {{PV}}$$ ( $$V_\text {{PV}}$$ ) measurements of SM55 mono-crystalline photovoltaic module.

Effect of module operating temperature on module efficiency in photovoltaic modules and recovery of photovoltaic module heat by thermoelectric effect

One of the parameters affecting the efficiency of photovoltaic (PV) modules and PV systems is the temperature. The factors that increase the temperature in PV modules cause loss of efficiency. In this study, experiments have been conducted with the aim of re ducing the module temperature. For this purpose, four polycrystalline and four monocrystalline PV modules, all with the same features, were used. A pair of polycrystalline and monocrystalline modules were used as reference modules. The aim of this study is to reduce the operating temperature of the modules, while also decreasing the transient temperature fluctuations in the system, in order to prevent the loss of efficiency. For this reason, current, voltage and power values of PV modules have been examined and the relationship between these values and module temperature has been explained. As a result, temperature values were measured at 30-80°C in reference modules, 30-50°C in heat pipe modules, 30-37°C in modules using heat pipes and phase-changing material, and 30-66°C in modules using phase-changing material with flexible surfaces. If the PV module operating temperature is increased by 35°C, the module efficiency decreases by 10%. Heat pipe and PCM balance the temperature in PV/T/PCM monocrystalline and polycrystalline modules. In PV/T/PCM modules, efficiency loss caused by temperature increase is 1%. In addition, electrical energy is produced from the heat accumulated on the surface of the PV module by means of Thermoelectric Generator (TEG). When the temperature difference between the surfaces is 15°C, the naturally cooled TE provides 0.45V energy output, while the forced-cooled TEG provides 0.97V energy output. As the temperature gap between the surfaces increases, the voltage and current values of the TEG also increase. Briefly, TEG’s power values increase up to 5W depending on the temperature gap between surfaces.

Thermal management of a mono-crystalline PV/T system using gold plasmonic nanofluid based optical filter

Solar energy can fulfill most of the world's electrical and thermal energy demands. The utilization of nanofluids in solar Photovoltaic/Thermal (PV/T) systems, to enhance the overall system performance using passive and active methods, have been studied explicitly in the last few years. More recently, nanofluid-based optical filters are integrated in decoupled fashion with Photovoltaic (PV) systems for the effective utilization of solar spectrum i.e. below and beyond the band-gap of PV cells. For the work presented here, we compared thermal performance of Au nanofluid-based optical filter (at 0.0002 wt%)over base fluid water on a 50 W mono-crystalline PV module under real outdoor conditions. The study results showed that in comparison to DI water, Au lowers the average surface temperature of the PV module, and hence better overall system efficiency compared to water as an optical filter. The overall efficiency of PV/T system was observed about 42%, 37% and 14% with Au nanofluid optical filter, de-ionized water filter, and bare PV module, respectively. This study revealed that the overall efficiency of the PV module with Au nanofluid as the optical filter can be enhanced.

Temperature Effects on Optimal Performance of PV Module

The commonly used renewable energy source (RES) is solar energy. However, the production of this energy from PV modules has a lot of challenges and still needs technological improvement. This research investigates the effects of temperature on Photovoltaic (PV) module optimal performance. An experimental setup of a Monocrystalline (MC) module was used and data on the temperature and other parameters were measured using appropriate measuring tools. The relationship between module temperature and other parameters was evaluated using Pearson product correlation. The findings of this study showed that the temperature is significant for the Monocrystalline PV module to operate at its optimal. Also, the finding revealed that there is a weak correlation between the open circuit voltage (OCV) of the panel and the temperature, however, the PV module temperature has a strong and positive correlation with other parameters namely; solar irradiance, short circuit current (SCC), output power and conversion efficiency (CE) with a correlation coefficient (CC) of 0.94, 0.93, 0.92 and 0.93 respectively. The conversion efficiency of the PV module increases when its temperature is within the maximum operating temperature and tends to decrease when the temperature is beyond the design operating temperature of the module. This implies that temperature is also a key parameter to consider when designing a PV module system for optimal performance. This research recommends that temperature should be considered in the design of PV modules to power any equipment or machines for better performance.

Computational Analysis of Temperature Effects on Monocrystalline PV Module using MATLAB

The world has moved from fossil fuels to renewable energy resources due to adverse environmental impacts, limited sources, and economic issues. It is not necessary that renewable energy sources have always led to many advantages but have drawbacks like weather dependency, unreliability, storage problems, and upfront costs. This study focuses on one of the major types of RES solar PV systems. The data is used from the specification of solar modules at Sukkur IBA University Sindh Pakistan. Solar photovoltaic output depends upon the weather conditions which vary from time to time resulting in variation in irradiance, temperature, power, and efficiency. This paper aims to observe the effects of the temperature ranging from 1 to 55°c on the efficiency of the monocrystalline photovoltaic module using MATLAB/Simulink. The performance parameters could be Open Circuit Voltage (VOC), Short Circuit Current (ISC), Maximum Power Point Current (IMP), Maximum Power Point Voltages (VMP), Fill Factor (FF), and Efficiency (η). Results from the simulation show that the estimated variation of silicon solar cell parameters such as VOC, IMP, series resistance, FF, and η decrease frequently with increasing temperature. And some parameters such as ISC, IMP, and temperature of the panel increase with rising ambient temperature.World has moved from fossil fuels to renewable energy resources due to adverse environmental impacts, limited sources, and economic issues. It is not necessary that renewable energy sources have always led to many advantages but have drawbacks like weather dependency, unreliability, storage problems and upfront costs. This study focusses on the one of the major types of RES solar PV system. The data is used from the specification of solar modules at Sukkur IBA University Sindh Pakistan. Solar Photovoltaic output depends upon the weather conditions which varies time to time resulting variation in irradiance, temperature, power, and efficiency. This paper aims to observe the effects of the temperature ranging 1 to 55°c on the efficiency of the mono-crystalline photovoltaic module using MATLAB/Simulink. The performance parameters could be as open circuit voltage (VOC), short circuit current (ISC), maximum power point current (IMP), maximum power point voltages (VMP), Fill Factor (FF) and efficiency (η). Results from simulation shows that the estimated variation of silicon solar cells parameters such as open circuit voltages, maximum power point voltages, series resistance, fill factor and efficiency decrease frequently with increasing temperature. And some parameters such as short-circuit current, maximum power point current and temperature of the panel increases with rising ambient temperature.

Fundamental study on the impacts of water-cooling and accumulated dust on photovoltaic module performance

<span>Photovoltaic (PV) modules have been becoming well-spread recently as alternative clean energy sources to traditional energy sources due to their efficiency and sustainability benefits. This paper applied various water temperatures and artificial dust levels to a couple of monocrystalline PV modules under outdoor conditions to observe their performance. Two different IV tracers were connected separately to each module for comparison purposes. Two temperature sensors were installed at the back of the panels to observe the cell temperatures. Besides, a temperature sensor was specified for ambient readings. Water flowed through an adjustable water-flow sensor to cool the overheated PV module using specific mass flow rates. The results indicate that the efficiency of the PV module starts to reduce when the panel temperature begins to surpass 49.1°C. It was discovered that cooling the PV module increases its efficiency from 0.97 percent at the lowest rate to 4.70 percent at the highest rate. Furthermore, accumulated dust on the PV module top surface can be reduced up to 3-fold under 110 g/m2 of dust, and up to 29.30% under 10 g/m<sup>2</sup> of 100% of its generated energy. Improvement techniques and future work on PV module performance are also discussed.</span>

PSOPruner: PSO-Based Deep Convolutional Neural Network Pruning Method for PV Module Defects Classification

Photovoltaic (PV) modules can be damaged by external environment, which can significantly reduce power generation efficiency. Electroluminescent (EL) imaging is an economical and widely applied technique for PV module defects detection. The analysis of EL images, however, is still labor-consuming. To solve this problem, a deep convolutional neural network (DCNN) is proposed to automatically detect and classify defects. The proposed DCNN performs well on a large public EL dataset with more than 2600 images extracted from both monocrystalline and polycrystalline PV modules. Nevertheless, the proposed DCNN cannot be directly applied on portable or embedded devices due to its requirement of large-size memory and intensive computation. To handle this challenge, an evolutionary algorithm-based DCNN pruning method, dubbed PSOPruner, is further developed. The pruning problem of DCNN is formulated as a search problem, which is solved by particle swarm optimization (PSO) algorithm. To improve the quality of the pruning scheme, a tailored trick is considered that the automatic searching process with PSO algorithm is repeated for multiple rounds. To illustrate the effectiveness of the proposed PSOPruner, we compare it with mainstream DCNNs and lightweight CNNs in terms of model complexity and model accuracy. Experimental results demonstrate that the proposed method could efficiently reduce the amount of model parameters with slight drop of accuracy.

AUTOMATICAL MEASURING DEVICE FOR RESEARCHING THE ELECTRICAL CHARACTERISTICS OF PHOTOELECTRIC MODULES

The article describes the developed and manufactured measuring device for measuring the electrical characteristics of photovoltaic modules depending on their temperature and radiation spectrum. The measuring device consists of a hardware and a software part. The basis for the hardware part is a personal computer with a built-in measuring board of a 16-bit analog-to-digital converter. The analog-to-digital converter processes signals from measuring current, voltage and temperature converters. As measuring current converters, shunts made of high-precision non-inductive resistance resistors were used. To measure a voltage greater than 5 V, dividers of the НP-9258 and НP-9251 type with conversion factors of 1:100 and 1:10, respectively, were used. The measuring device controls the load made of non-inductive active elements. In order to change the spectral composition of radiation, four light filters are used, which transmit light with wavelengths in the red, yellow, green and blue region of the spectrum. After replacing them on the radiation source, the energy of the incident radiation must be set at the level of 1000 W/m2. The software that provides the measurement process is written in the Delphi programming language and works, according to the algorithm, in automatic and manual modes. Using the measuring device the volt-ampere and volt-watt characteristics of the photovoltaic module were obtained depending on its temperature and radiation spectrum. The measuring device works in manual and automatic modes. In manual mode you can measure at least one volt-ampere characteristic, and if necessary, any number of them. In automatic mode, measurements of the current-voltage characteristics of the photovoltaic module are performed as many times as necessary to complete the transition process of heating the photovoltaic module to a certain temperature. The developed measuring device was used to study the monocrystalline photovoltaic module. The volt-ampere and volt-watt dependences of the photovoltaic module were obtained, depending on its temperature and radiation spectrum. Conclusions were made regarding the sensitivity of the photovoltaic module to the spectrum of radiation in the visible range and the decrease in energy efficiency with increasing temperature.

Temperature Estimation of Partially Shaded Photovoltaic Modules Using a Multiphysics Model

Partial shading is common in both photovoltaic (PV) stations and building integrated PV systems. The temperature increase of partially shaded (PTS) module not only reduces its efficiency but also accelerates its degradation. Therefore, temperature estimation of PTS module is essential for assessment and maintainence of PV systems. In this article, a multiphysics model consisting of an electrical model, an optical model, and a thermal model is developed. Particularly, the parallel circuit is adopted for the PTS cell, making it possible to calculate the electric power and heat generation of shaded region and unshaded region in the PTS cell, respectively. To the best of our knowledge, it is the first attempt to estimate the temperature distribution of PV module with PTS cell. Experiments are conducted on monocrystalline PV modules. One specific cell is partially shaded in various proportions and environmental conditions. The maximum temperature on the front surface of the PTS module is measured with the infrared thermographic camera and also calculated by our method. The root mean square error is 6.14 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> C, which verifies the effectiveness of the proposed multiphysics model for temperature estimation of PTS modules.