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Increased temperature of photovoltaic (PV) module decreases its performance; hence, integration of the cooling system is imperative in minimizing this detrimental effect. In this study, passive cooling of PV module with different heatsinks has been simulated by thermal models using ANSYS STEADY-STATE THERMAL software. The results were based on the effect of convective heat transfer coefficients from 5 to 1000 W/m2K for the temperature reduction of PV module using 19 different heatsinks. Three configurations: flat plate heat spreader, fin-only heatsinks, and fin-flat base plate combined heatsinks, have been studied at 35 °C ambient temperature and 800 W/m2 solar radiation. The result shows that at convective heat transfer coefficient of 10 W/m2K, the combined type model C7, and the fin-only type model B4 demonstrated around 18.94% and 9.36% lower PV cell temperature, respectively, than the flat plate type model A2. Moreover, C7 and B4 models had about 67.5% and 78.03% less material weight than the A2 model, making the heat spreader type least feasible compared with the other two. The temperature contours of the PV cell layer at a given operating condition showed uniform distribution for both flat plate types and combined types. In contrast, the fin-only heatsink configuration illustrated hotspots within the PV cell layer. [ABSTRACT FROM AUTHOR]

The operational temperature highly influences the efficiency of the solar photovoltaic (PV) module, in which high temperature decreases the output power accordingly. In this work, a polycrystalline PV module is modified using a finned phase change material (PCM) panel attached to the rear as a thermal energy storage unit to decrease and regulate the operating temperature under hot weather conditions in southern Iraq. For this purpose, local Iraqi paraffin wax is used as a PCM loaded into a galvanized steel panel that has internal smooth wavy fins to improve the PCM poor thermal conductivity and accelerate its melting and solidification rates. Experimental results showed that the modified PV module temperature is decreased by up to 16°C compared with the reference PV module, resulting in maximum output power of up to 38.4% more than an identical reference PV module. Moreover, the electrical efficiency of the modified PV module is improved respectively by 34% and 37.2% on the first and second day of the experiment over the reference PV module, indicating remarkable electrical and thermal performance improvement. [ABSTRACT FROM AUTHOR]

Featured Application: The model developed in this work has practical applications for simulating the operation of non-standard multi-junction photovoltaic modules with radiation concentrators. The silicon photovoltaic modules that dominate the market today are constantly being modified, but at the same time, the search for new, more efficient design solutions is underway. The study examined a less popular photovoltaic module built from point-focusing Fresnel radiation concentrators and high-efficiency three-junction cells. The advantage of this type of module is its high overall efficiency, exceeding 30%. The disadvantage is that they require biaxial precision tracking mechanisms because even a small deviation of the direction of direct solar radiation from the perpendicular to the module's surface causes a large and abrupt drop in efficiency. This type of photovoltaic module structure is often also marked with the symbol C3PV. A mathematical model and simulation calculations were carried out in the Matlab/Simulink package for the C3PV module—the CX-75/200 model based on the "Solar Cell" component. The concentration of direct solar radiation was taken into account. For the module under consideration, experimental and simulation results show the necessity of accurate positioning concerning the direction of solar radiation—deviation of the radiation angle by about 5° causes a very high power loss (by about 92%). [ABSTRACT FROM AUTHOR]

• Backsheet (BS)/ethylene vinyl acetate (EVA)/backsheet laminates containing different vinyl acetate (VA) contents (18, 24, 33 and 40 wt%) have been prepared and subjected to the damp heat ageing (i.e., 85 °C temperature and 85% relative humidity) for 1000 h to study the effect of DH ageing and VA content on the interfacial adhesion strength. • The adhesion strength is found to improve for laminates containing EVA18 while, it is found to reduce for the laminates containing EVA33 and EVA40. The adhesion strength is found to be unchanged for EVA24 after the ageing. • The gel content analysis has indicated an increase in the degree of cross-linking for EVA18 and a decrease in the EVA40 after the ageing. • Through XPS analysis it is found that the failure mode at the BS/EVA18 interface is delamination type in the unaged condition and alter to the cohesive type after the ageing. On the other hand, the failure mode for BS/EVA40 remains to be cohesive both before and after the ageing. • This study indicates that the durability of the adhesion strength at the BS/EVA interface is higher for the films containing lower VA content than the films containing higher VA content. Ethylene vinyl acetate (EVA) is an effective encapsulant to adhere various layers in the photovoltaic (PV) module. In this study, we have fabricated EVA films containing different vinyl acetate (VA) content (18%, 24%, 33% and 40%) and laminated between two layers of backsheet (BS). These laminates have been subjected to damp-heat (DH) ageing at 85OC and 85% relative humidity (RH) for 1000 h to evaluate the change in adhesion strength at EVA/BS interface using the T-peel test. The adhesion strength for EVA containing 18% VA content has been found to improve but it deteriorates for EVA with 33 and 40% VA content after ageing. However, adhesion strength for EVA containing 24% VA content is found unaffected after ageing. The degree of cross-linking and VA content have been determined through gel content measurement and thermo-gravimetric analysis (TGA) respectively. The degree of cross-linking and VA content increases significantly in EVA18 but decreases in EVA40 due to DH ageing. The chemical changes have been examined by the Fourier transform infrared spectroscopy (FTIR) and the X-ray photoelectron spectroscopy (XPS). The failure mode (cohesive or delamination) at the interface and its correlation with the adhesion strength has been explored using XPS. The failure mode at the EVA18/BS interface alters from delamination type in pristine condition to the cohesive type due to DH ageing. However, the failure mode for EVA24 and EVA40 is found to be cohesive in both the pristine and aged condition. [ABSTRACT FROM AUTHOR]

Thermal delamination – meaning the removal of polymers from the module structure by a thermal process – as a first step in the recycling of crystalline silicon (c-Si) photovoltaic (PV) modules in order to enable the subsequent recovery of secondary raw materials was investigated. A correlation between treatment temperature and duration was established by an iterative process. Furthermore, chemical characterization of the resulting solid outputs (glass, cell, ribbons and residues) was performed in order to assess their further processing options. Additionally, the effect of removing the backsheet as a pre-treatment before the actual delamination process was investigated in relation to the aforementioned aspects of treatment duration and output quality. Results show that increased temperatures reduce the necessary treatment duration (65 minutes at 500°C, 33 minutes at 600°C) while generating the same output quality. The backsheet removal leads to an additional duration decrease of more than 45% at each considered temperature, while also having positive effects relating to fewer solid residues and easier flue gas handling. In regard to the main output specifications no significant influence of the pre-treatment is observed. Overall thermal delamination can be seen as a feasible method in order to obtain high value secondary raw materials from c-Si PV modules, while backsheet removal as pre-treatment should be considered as advantageous from multiple standpoints. [ABSTRACT FROM AUTHOR]

In the given article the methodology of making a photovoltaic module mathematical model is presented, which lets reproduce its energy characteristics in real operating conditions. Also, the major types of mathematical models of photovoltaic converters are discussed and most well-known estimation methods of their parameters are analyzed. An original and simple way of parameters definition of photovoltaic module is introduced based on the technical specification data without using programming and developing numerical estimation algorithms. The suggested method is easily realized in the tabular program Excel with installed tool «Search for solutions». The simulation results of volt-ampere characteristic (V-I curve) of photovoltaic module Kyocera KC200GT are presented in a wide variation range of temperature and illumination. In addition, an accuracy evaluation is made by comparing the model characteristics and experimental data. The model was tested on a number of photovoltaic modules and proved good modeling results compliance with manufacturer's data. The model provides a high modeling accuracy around MPP (maximum power point). This fact allows to use it for development of effective algorithms for photovoltaic power stations controllers, circuit design advancement of converting devices, prediction of power generation, operating modes analysis and optimization for photovoltaic systems. [ABSTRACT FROM AUTHOR]

The field‐measured current–voltage (I–V) curves of photovoltaic (PV) modules need to be corrected to Standard Test Conditions (STC) in order to estimate the degradation rates. STC correction procedures have various attributes such as accuracy, requirement of minimum number and types of I–V curves, required irradiance range, and the type of correction (specific points or entire I–V curve) that determine their optimality for specific applications. This paper presents the investigation of accuracy and constraints of six different STC correction procedures for high‐throughput field I–V measurements through experimental and simulation studies. Following STC correction procedures are considered in this paper: IEC 60891‐Procedure 1, IEC 60891‐Procedure 2, Modified IEC 60891‐Procedure 1, Standard Irradiance and Desired Temperature (SIDT) procedure, Anderson procedure, and Voltage‐Dependent Temperature Coefficient (VDTC) Procedure. Eight different simulation models for predicting the performance of PV modules at arbitrary irradiance and temperature are compared, and the simulation model that yields lowest root mean square error and the most accurate estimation of power temperature coefficient is identified. The simulated I–V curves using this model and the experimentally measured I–V curves on a flash tester at different temperatures and irradiances are provided as an input to all of the STC correction procedures. The average percentage errors in correction of maximum power (Pmax), open‐circuit voltage (Voc), short‐circuit current (Isc), and fill factor (FF) were determined as a function of irradiance and temperature during measurement. Systematic biases introduced during correction by certain procedures were also identified. Based on the error estimation, constraints of various procedures, and requirements of high‐throughput field I–V measurements, the most optimal STC correction procedure was identified. Moreover, the analysis of the root cause of superior performance of this procedure is also presented. [ABSTRACT FROM AUTHOR]

The relevance of research is caused by the increase of the number of photovoltaic power plants in the Republic of Belarus and, accordingly, the need to solve problems of diagnostics of photovoltaic modules. A new Simulink model of a photovoltaic module focused on using the standard SimPowerSystems library of power supply system elements (a part of the MatLab/Simulink) is proposed. The model allows altering solar irradiation values for each solar cell of the module. The use of the model also makes it possible to obtain calculated values of voltages and currents at the photovoltic module output. In addition, the model provides the simulation of individual solar cells shading in the module. The developed Simulink model operates on the base of a well-known exponential dependence describing the volt-ampere characteristic of a photovoltaic module, and also takes into account the real circuit of the module with bypass diodes. The series resistance of the photovoltaic module is calculated by the subtraction between its experimental and theoretical volt-ampere characteristics for conditions that are close to normal. The Simulink model of the SF-P672300 module contains 72 nonlinear elements implemented on the basis of controlled current sources and connected in series. The model solved the problems of the algorithm stability for calculating algebraic cycles by introducing constraint the current and the voltage parameters. Experimental studies for the fully illuminated and partially shaded SF-P672300 module have demonstrated that the maximum relative error of the developed Simulink model does not exceed 15 %. Experimental and theoretical current-voltage characteristics of the SF-P672300 module under full illumination and partial shading are presented. The presented Simulink model may be used both at the design stage and at the operation stage of photovoltaic power plants in order to simulate and analyze the factors that affect the operation of them.

An experimental study has been conducted to reduce the loss of efficiency caused by the increase in temperature in photovoltaic (PV) modules. The aim of this study is to decrease the instantaneous temperature changes and overall mean temperature in the system to prevent the uncontrolled increase of the module temperature, while reducing the loss of performance caused by the increase in temperature. The experiment was carried out by using a pair of polycrystalline and a pair of monocrystalline PV modules. Both types of the PV modules had 10W power and exact same features. A reference/control module has been selected from each type of PV modules and these control modules has been added to the system as traditional PV modules. Heat pipe and phase changing material were applied to the back surface of other PV modules. The phase changing material was used to store heat on the PV module surface and to transfer the stored heat to the heat pipe. Calcium Chloride Hexahydrate was the preferred material to use as the phase change materials in the system. The system temperature was then brought under control by passing water through the heat pipe in the system. The temperature measured on the surface of the reference/control module was 30-80ᵒC during the day, while the temperature ranged between 30-40ᵒC in the experimental modules with phase changing substance. We found that performance loss caused by increase in surface temperature in reference/control modules reaches up to 20%. Whereas, the performance loss in the experimental modules is only as high as 1% under the same conditions. The mean temperature of the active PV modules has been reduced by using heat pipes and phase changing material. Lowering the mean temperature subsequently reduced the loss of performance caused by the increased temperature.

Bu çalışmada, fotovoltaik panellerin performans parametrelerine (kısa-devre akımı, açık-devre gerilimi ve maksimum çıkış gücü) ait sıcaklık katsayılarını elde etmek için yeni bir yöntem ortaya konmuştur. Eğri uydurma tekniğine dayanan bu yeni yöntem, ölçülen ve hesaplanan performans parametreleri arasındaki en küçük hata değerlerini sağlayan sıcaklık katsayılarını elde etmektedir. Yeni yöntem silikon tabanlı bir fotovoltaik panel için test edilmiştir. Bu panelin; yeni yöntemden elde edilen sıcaklık katsayıları ve kataloğunda sunulan sıcaklık katsayıları dış ölçülen performans parametreleri kullanılarak ortalama karekök hata yaklaşımı ile karşılaştırılmıştır. Sonuç olarak, yeni yöntemden elde edilen sıcaklık katsayılarının, katalog sıcaklık katsayılarından daha iyi bir doğrulukla performans parametrelerinin sıcaklık bağımlılığını ifade ettiği ortaya konmuştur. Mevcut yöntemlerden farklı olarak, yeni yöntem sıcaklık katsayılarını elde etmek için sabit parametrelere, belirli kısıtlamalara veya ilave bir deneysel düzeneğe ihtiyaç duymamaktadır.

The solar photovoltaic industry has developed rapidly in recent years. Accurate diagnosis of the location and type of PV module faults can improve the efficiency of operation and maintenance personnel. In this paper, a deep learning diagnostic model based on convolutional neural networks-long short term memory(CNN-LSTM) is proposed, which can be used to complete the detection task. In this paper, a fault classification method based on current performance is established. The algorithm firstly designs a feature extraction algorithm based on the layout characteristics of the PV array, and extracts the lateral and vertical features of the PV array current to obtain the spatial and temporal characteristics. The CNN network further extracts the lateral features and compresses the vertical features to solve the problem of single feature types and slow training. Finally, the LSTM neural network is used to complete the fault diagnosis of the PV modules.

I n concentrated photovoltaic thermal CPVT systems, sunlight is directly converted into electricity and during this conversion waste heat is generated on the photovoltaic module. The resulting waste heat can be used for heating the fluids. In this study, the effect of using a low concentrating photovoltaic thermal system as a pre-heater before the evaporator in the organic Rankine cycle ORC was investigated. Thermodynamic analyzes were performed for different solar radiation values, concentration ratio values and various photovoltaic module PV materials. The increase in solar radiation and concentration increased the electricity production in the photovoltaic module and the thermal efficiency of the system but led to a decrease in exergy efficiency. In the analyzes, four different PV module materials were examined and M-Si and P-Si module materials showed better performance in terms of system efficiency and electricity production

As a representative new energy source, solar energy has the advantages of easy access to resources and low pollution. However, due to the uncertainty of the external environment, photovoltaic (PV) modules that collect solar energy are often covered by foreign objects in the environment such as leaves and bird droppings, resulting in a decrease in photoelectric conversion efficiency, power losses, and even the “hot spot” phenomenon, resulting in damage to the modules. Existing methods mostly inspect foreign objects manually, which not only incurs high labor costs but also hinders real-time monitoring. To address these problems, this paper proposes an IDETR deep learning target detection model based on Deformable DETR combined with transfer learning and a convolutional block attention module, which can identify foreign object shading on the surfaces of PV modules in actual operating environments. This study contributes to the optimal operation and maintenance of PV systems. In addition, this paper collects data in the field and constructs a dataset of foreign objects of PV modules. The results show that the advanced model can significantly improve the target detection AP values.

This study introduces a novel machine learning (ML) method utilizing a stacked auto-encoder network to predict stiffness degradation in photovoltaic (PV) modules with pre-existing cracks. The input data for the training process was derived from numerical simulations, ensuring a comprehensive representation of module behavior under various conditions. The findings highlight the robust predictive capability of the model, as evidenced by its impressive R 2 value of 0.961 and notably low root mean square error (RMSE) of 4.02%. These metrics significantly outperform those of other conventional methods, including the artificial neural network with R 2 of 0.905 and RMSE of 9.43%, the space vector machine with R 2 of 0.827 and RMSE of 17.93%, and the random forest (RF) with R 2 of 0.899 and RMSE of 11.02%. Moreover, the findings suggest that the predictive dynamics of degradation are affected by the varying weight functions of different input parameters, such as climate temperature (CT), grain size (GS), material effort, and pre-crack size, as the degradation level changes. Furthermore, a geometric analysis reveals model deficiencies where significant overestimations correlate with thicker glass components, while pronounced underestimations are predominantly associated with thinner layers of polycrystalline silicon wafer and Ethylene Vinyl Acetate in the module. As a case study, it demonstrated that to maintain a constant degradation level between 1.30 and 1.32 in a PV module with components featuring consistent geometric attributes, the input parameters must be kept within specific ranges: CT ranging from 33 °C to 57 °C, GS ranging from 36 to 81 μ m, material effort ranging from 0.74 to 0.81, and pre-crack size ranging from 24 to 32 μ m. Therefore, this underscores that the ML model not only predicts degradation but also delineates the parameter space required to achieve a consistent output value., (© 2024 IOP Publishing Ltd.)

In this study, a thermodynamic model for concentrated semi-transparent-photovoltaic thermoelectric generator (CSPV-TEG) hybrid power generation system has been developed. Using the model, solar cell temperature, exergy and electrical efficiency of the hybrid system, temperature difference across TEG, power output and photovoltaic conversion efficiency of the PV module and the electrical efficiency of the TEG module have been calculated. The simulation of the system, using MATLAB, was conducted for clear day in May for New Delhi by varying the concentration ratio (C) and the number of p-n thermocouples (N). The results illustrate that for the hybrid system, maximum power output of 219.75 W was obtained for C = 2 N = 200 case and peak electrical efficiency of 10.44% was obtained for C = 1 N = 200 case. The peak value of the exergy efficiency of the hybrid system exceeded the peak value of electrical efficiency of the hybrid system by 1.33%. [ABSTRACT FROM AUTHOR]

This work is devoted to studying the energy characteristics of a solar collector with a selective receiving surface. The use of special technologies of plating high-quality selective coatings on the heliocollector absorber makes it possible to substantially increase the coefficient of conversion of the solar radiation incidence flux. The research data are presented on the flat heliocollectors, which serve to heat-up a heat carrier used mainly for the needs of the hot-water supply for the individual consumers. In the performed experiments, the flat solar collectors were equipped with copper and stainless-steel absorbers. The studies showed that the heliocollectors can ensure better use depending on the operation mode of the entire system of the solar hot-water supply. The experiments were carried out by the staff of the Renewable Energy Sources and the Electric Energy and Networks department of Sevastopol State University at the Institute of Nuclear Energy and Industry. It was shown that the conversion coefficient of the solar power plants for the direct conversion of the radiation flux into thermal energy is far more energy efficient compared to that of the solar electric generation systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • Translation equations introduce bias in the power and device parameters of a module. • Device parameters transform algebraically with irradiance and temperature. • Module degradation assessment, based on translated I-V curves, is not advisable. Photovoltaic modules are rated at standard test conditions, STC, but in real life operation they are exposed to very different conditions. The power of a module and its device parameters are obtained from the current-voltage characteristic (I-V curve) of the module but the curve varies with irradiance and temperature conditions. The I-V curve is transformed from real operational conditions to STC and vice versa with translation equations. In this paper we investigate the fundamental nature of the translation equations and show that they introduce consistent bias in the power and device parameters, obtained from the translated I-V curves. We show that the nature of the translation equations forces the device parameters to transform from one to another set of irradiance and temperature conditions by algebraic transformations, which are derived in this paper. Validation of our findings is given for the series resistance. Our findings have significant implications for the assessment of module degradation. [ABSTRACT FROM AUTHOR]

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In this study the results of the analysis of the dependence of the temperature of solar cells (SCs) and thermoelectric generators (TEGs) and the overall electrical and thermal efficiency of the PVT–TEG combined system on thermal characteristics and environment are presented. The hot side of a TEG module is attached to the back side of the photovoltaic module (PVM). The heat carrier circulating through the absorber cools down the cold side of the TEG module, where the temperature gradient is converted into additional electrical energy. The mathematical model for a PVT–TEG combined setup was realized in the MathCAD program. The agreement between numerical calculations and experimental data was analyzed using the "goodness of fit." Experimental measurements were carried out at the Heliopolygon at Tashkent State Technical University. The solar radiation flux density, ambient temperature, wind speed, open circuit voltage, short-circuit current, temperatures of the PVM, the thermo-electromotive force, and the current of TEG were measured without and with reflectors oriented to the south at a horizontal angle of 25°. However, in order to verify the model, the calculated and experimental data of the output power of the combined PVT–TEG setup were compared. It was revealed that the root-mean-square deviation (RMSD) of the peak power of the experimental and calculated data was 1.74 W, or 4.8%. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) solar energy enables direct production of electricity. The photovoltaic effect produced in the solar cells converts light energy from the sun's rays into electricity. Some of the solar radiation absorbed by a PV module is not converted into electricity but takes the form of an increase in the temperature of the module, reducing its electrical efficiency. The operating temperature of PV modules generally affects the performance of the PV system; performance also depends on numerous variables such as ambient temperature, wind speed, wind direction, total irradiance, dust accumulating on the PV module face and relative humidity. In this study different models for predicting the operating temperature of PV modules have been investigated. The models' relevance to PV module technology and climatic conditions in Errachidia city (coordinates: 31° 55′ 55″ north, 4° 25′ 28″ west) in the Drâa Tafilalet region was examined. The models that factor in wind data predict PV cell temperature better than the standard approach which does not include wind data. The models' accuracy was estimated based on R2 and RMSE values. A model is more accurate the higher the R2 is and the lower the RMSE is. In addition, we noticed that the models investigated are more accurate for a short time period during the day.

Over the past few decades, a considerable number of studies have been reported on assembly lines or less automated factories. Little attention has been given to implementing lean tools to a highly automated manufacturing environment. It is, therefore, necessary to make a more highly automated factory lean by considering both the manufacturing system variability and demand uncertainty. The purpose of this paper is to propose an effective lean tool to help practical lean participants successfully implement lean practices in a highly automated manufacturing environment. This study presents an example of how lean standard work is implemented and the throughput of a pacemaker workstation is improved by solving the low work-in-process buffer problem. A practical case from a photovoltaic module process with a semi-automated production line is used to illustrate the proposed method. The implementation results are promising. They showed a 37.5% labour reduction prior to the pacemaker workstation and a 304.7% increase in the daily throughput at the bottleneck workstation. [ABSTRACT FROM AUTHOR]

Infrared thermography is the science of measuring the infrared energy emitted by an object, translating it to apparent temperature variance, and displaying the result as an infrared image. Significantly, acquiring thermal images delivers distinctive levels of temperature differences in solar panels that correspond to their health status, which is beneficial for the early detection of defects. The proposed algorithm aims to analyze the thermal solar panel images. The acquired thermal solar panel images were segmented into solar cell sizes to provide more detailed information by region or cell area instead of the entire solar panel. This paper uses both the image histogram information and its corresponding cumulative distribution function (CDF), useful for image analysis. The acquired thermal solar panel images are enhanced using grayscale, histogram equalization, and adaptive histogram equalization to represent a domain that is easier to analyze. The experimental results reveal that the extraction results of thermal images provide better histogram and CDF features. Furthermore, the proposed scheme includes the convolutional neural network (CNN) for classifying the enhanced images, which shows that a 97% accuracy of classification was achieved. The proposed scheme could promote different thermal image applications—for example, non-physical visual recognition and fault detection analysis. [ABSTRACT FROM AUTHOR]

The article considers the issues of developing a monitoring system for electrical power and energy consumption of rural households in order to obtain reliable data on daily, monthly and annual loads, the wind velocity and direction, current and voltage from a photovoltaic module, which are necessary for developing a methodology for choosing equipment for a power supply system based on renewable energy sources (RES) for rural households in central region of Russia. [ABSTRACT FROM AUTHOR]

The recent Covid-19 pandemic and its required hygiene protocols further revealed the importance of ventilation process in all buildings deal with human life. Solar Chimney Ventilator (SCV) is a type of renewable technology that is able to provide natural ventilation for the buildings. However, conventional SCV is not economical due to its low performance of ventilation. Thus, in the current study, an innovative tilted Solar Chimney Ventilator with Phase Change Material integrated with Photovoltaic technology (SCV-PV-PCM) is proposed and investigated under real unsteady transient weather condition (based on Hong Kong climate) via a validated three-dimensional numerical study. The characteristics of the SCV-PV-PCM is analyzed during the day (through different month i.e March, June, September, and December) and compared with conventional SCV-PV system. Based on the findings, the produced power and ventilation capacity of the SCV-PV-PCM is higher than those for the common SCV-PV system. Nonetheless, the system is not able to provide the appropriate ventilation power for the building through the winter due to lack of high ambient temperature and strong solar radiation. Moreover, it is concluded that using the SCV-PV-PCM in the building is most economically beneficial in the month of June by saving 2.88 $/month. [Display omitted] • Performance of the novel system of SC-PV-PCM is studied. • The performance of the SC systems is evaluated at different seasons of Hong Kong. • The overall performance of the novel system is higher than the SC-PV system. • Using PCM increases the electrical performance of the solar chimney. • Using the SC-PV-PCM system leads to money-saving at different seasons. [ABSTRACT FROM AUTHOR]

• Improved passive cooling of the PV module through understanding of wind speed and flow direction. • Effect of air turbulence on module temperature. • More power generation of PV module with reflector system in the reduced operating lifespan. The effective use of the available land in a PV power plant can be obtained by the integration of a commonly available flat stainless-steel reflector. The integration of the reflector increases module temperature and simultaneously the degradation rate. In this regard, the present work proposes a 3-D opto-thermal simulation model to analysis the performance of the commercial C-Si PV module with stainless steel (SS) reflector. The study also highlights that the natural flow of wind effectively reduces the elevated temperature and the direction of wind flow plays a very prominent role in heat evacuation. Incidentally, the largest state of India, Rajasthan has plenty of promising light breeze throughout the year and that is to come from the mostly north or west direction. A simpler version of the proposed model was experimentally validated in the month of July in Jaipur, India. The simulation result shows that the reflector induces 30 °C to 40 °C increment in temperature in the PV module for laminar airflow. Considering the turbulent airflow model, the temperature rise is 10–20 °C. The thermal scenario largely depends on wind flow and the season considered. The lifetime of the PV module is reduced from 25 years to 21 years with the integration of reflector at favorable wind flow condition. However, it generates a significantly more electric power which overcomes the lifetime loss. [ABSTRACT FROM AUTHOR]

Regarding the global increasing trend of photovoltaic (PV) installations, it is necessary to examine their performance under different climatic conditions. In this study, a three years of experimentation was carried out in order to evaluate soiling loss, yearly degradation and economic viability of PV systems in the south-central Iran. The results showed that dust effect in consecutive years can be significantly different. For instance, soiling loss in summer of 2017 and 2019 was 6.9% and 7.7%, respectively, whereas this value was 26.4% in summer 2018 due to a sand storm. The yearly average degradation of PV module was evaluated 1.17%, which was significantly lower than the degradation rate found by considering only first two years operation of PV module. In the economic analysis part of the research, a typical 1 MW solar plant was modeled in PVsyst software by using the measured data. The economic assessment showed that investment in PV industry without any special government support is economically profitable, as net present value (NPV) and discounted payback time (DPT) were found 1,367,499 US$ and 5.82 years, respectively. Also, levelized cost of electricity (LCOE) was 0.099 US$/kWh, which could be reduced to 0.054 US$/kWh by providing loan for investment costs. • Long-term averages of soiling loss and yearly degradation of PV modules were found. • Economic study of a PV plant was conducted using measured data and simulation tools. • Yearly average soiling loss was in the range of 4.2–8.6%. • Yearly average degradation of PV modules was evaluated to be 1.17%. • Low interest loans for a PV project could decrease LCOE by up to 45.5%. [ABSTRACT FROM AUTHOR]

The authors report on the light‐ and elevated temperature‐induced degradation (LeTID) effect observed on bifacial photovoltaic modules and its potential impact on photovoltaic plants performance. Indoor LeTID quantification using indoor carrier‐induced degradation (CID) is carried out using current injection. Power measurements yielded higher LeTID sensitivity for the rear side of bifacial modules compared to the front side, hence leading to a variation of the bifaciality factor by several percentage points. The difficulty in evaluating the maximal power degradation caused by LeTID is also highlighted as a reduced number of samples are used most of the time and as cells within a single module do not have always the same performance evolution trends. Using indoor CID results with the help of empirical fitting and Arrhenius relation, the yield impact of LeTID on a bifacial power plant is simulated under three different climates. Modeling results help to identify the main parameters related to LeTID modules sensitivity that impact photovoltaic (PV) plants yield: maximal power degradation, stabilized power value after regeneration, activation energy value, and LeTID kinetics. In some cases, the yield variation caused by LeTID sensitive modules could be mitigated by carefully selecting the modules as a function of climatic conditions. [ABSTRACT FROM AUTHOR]

In this study, a new method is introduced to compute the double-diode model parameters of commercially available photovoltaic modules. The new method has been based solely on datasheet-supplied electrical data. The new method offers two novelties. First, the dark reverse saturation currents are calculated analytically. Second, the parameters of the double-diode model are calculated by a new recursive procedure using tuning parameters. The validity of the new method is tested for twenty commercially photovoltaic modules with different technologies via the normalized root mean square error tool by comparing the datasheet current-voltage curves with simulated curves. In addition, the proposed method is compared with other methods at different operating conditions and also tested in the field under actual operating conditions using the root mean square error tool. It was founded that the new method calculates the parameters of the double diode model and simulates the current-voltage curves of commercially photovoltaic modules under various operating conditions with a high accuracy. Moreover, the new method is also very competitive with the selected methods and even achieves better simulation accuracy with a very low error level. The obtained results show that the new method is highly accurate, practical, and simple for all photovoltaic users. [ABSTRACT FROM AUTHOR]

• Field-exposed snail trails affected PV modules are examined. • Investigation is conducted at both the module and cell levels. • Uncover associated reliability issues and performance impacts. • Presence of snail trails could serve as an indicator of broader degradation concerns. The reliability of photovoltaic (PV) modules is critical in harsh outdoor environments, where they are exposed to various stresses that can cause various degradations. In recent decades, the frequently observed degradation called snail trails in crystalline PV modules, is enormous concern due to less clarity about its effects on PV module reliability and performance. In this work, field-exposed snail trails affected PV modules are examined. Investigation is conducted at both the module and cell levels to uncover associated reliability issues and performance impacts. Examination methods include visual inspection, current–voltage (I-V) characteristics, microscopic imaging, electroluminescence (EL) imaging, and dark-lock-in thermography (DLIT) imaging. Snail trails are found with different degradation modes, where cell breakage and shunt were found as likely occurred degradation along with the presence of bubbles and backsheet degradation. Also, the metallic fingers near to snail trails were found thinner and deteriorated. In EL imaging, characteristics pattern of snail trails was found out as a bright periphery along dark lines. DLIT imaging highlighted elevated temperatures along the snail trail path as a characteristic pattern. Performance losses in the snail trails affected PV modules and cells were attributed to various degradations that observed with snail trails. The findings suggest that the presence of snail trails could serve as an indicator of broader degradation concerns. This work is beneficial to understand the reliability issues and performance losses in snail trails affected PV modules. [ABSTRACT FROM AUTHOR]

This research facilitates the placement of solar and wind-powered distributed generators (RDGs) in an unbalanced 3-phase IEEE 25-node distribution system intended to minimize the total expense of buying electricity from the grid and releasing carbon dioxide over twenty years. The probability distribution functions of Beta and Rayleigh are employed to attain solar illumination and wind velocity in a particular region. Unbalanced voltage deviation (UVD) and harmonic flows (HFs) from non-ideal loads and RDGs are considered. Metaheuristic methods are coded in MATLAB to find RDGs' location and capacity, and then OpenDSS is used to calculate power and harmonic issues. As a result, the total expenses can be reduced to $1.4141 million, which is 10.7% of the base system's. Additionally, HFs and UVDs at every node follow the IEEE Std. 519 and the IEEE Std. 45-2002, respectively. So, the placement of RDGs has a beneficial position in unbalanced distribution systems. [ABSTRACT FROM AUTHOR]

Dust deposition density and particle size impact on PV module energy utilization was investigated. Module A was clean, and modules B, C and D were dusted with deposition densities of 6.94 g/m2, 13.88 g/m2, and 20.83 g/m2, respectively. Test-1 and test-2 were carried out with steel slag dust particles with a size of 61 μm and 109 μm, respectively. The decrease in energetic efficiency comparing module A was 2.45%, 3.99% and 5.9% for the B, C and D modules in test-1, respectively. In test-2, the decrease in energetic efficiency was 1.77%, 2.77%, 3.63% for modules B, C, and D. In test-1, the exergy efficiency of modules B, C, and D declined by 2.67%, 4.3%, 6.62%. In test-2, the exergy efficiency fell by 1.94%, 2.84%, 4.19% for modules B, C and D, respectively. The annual exergy destruction cost was calculated to be $49.97, $51.48, $52.42, and $53.78 for modules A, B, C, and D, respectively. For test-2, the corresponding values were $48.13, $49.2, $49.66, and $50.4 for modules A, B, C, and D, respectively. The decrease in energetic and exergetic efficiency was lowered by the particle size increase. The decrease in energetic and exergetic efficiency was raised by increased deposition density. [ABSTRACT FROM AUTHOR]

Photovoltaic module (PVM) only can utilize visible and ultra-violet parts of solar spectrum, constrained by the Shockley-Queisser limit. To fully use solar spectrum, in this study, solar selective absorber (SSA) and elastocaloric cooler (ECC) are gradually hybridized with PVM to form a new hybrid system for the first time. The performance metrics of PVM, ECC, and hybrid system, taking into account various irreversible effects, are mathematically derived. The hybrid system achieves approximately a 63% enhancement in both energy efficiency and power output density compared to a standalone PVM, outperforming other similar PVM-based hybrid systems. Exhaustive parametric studies show that increasing the operating temperature, solar irradiance, diode ideality factor, length ratio or section area ratio can enhance the hybrid system performance. The optimal combination of refrigerant and actuator materials are, respectively, Ni–Ti and Cu–Zn–Al alloys. Furthermore, a case study conducted to forecast practical performance under southeast China's weather conditions reveals that the hybrid system attains significant annual maximum energy efficiency and power output density, reaching 29.3% and 54.66 W m−2, respectively. The findings from this study provide valuable insights and recommendations for the optimum design and operation for such a hybrid system. • A new photovoltaic/thermal/elastocaloric hybrid system is theoretically developed. • The models of hybrid system and each subsystem are described and validated. • The hybrid system design can gain a 63% enhancement in energy efficiency. • Exhaustive parametric analyses on the performance of hybrid system are conducted. • A case study predicts the practical performance based on local weather conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • An advanced ultrasonic technique is employed to detect glass cracks in solar modules. • The Lamb waves scanning method produces map of the defects locations efficiently. • The investigated defects are due to mishandling, representing a real-world scenario. Ensuring the structural integrity of solar photovoltaic modules is crucial to maintain power production efficiency and fulfill the anticipated product lifespan. Hence, implementing quality control procedures and structural health monitoring is necessary throughout the stages of manufacture and operation. The ultrasonic examination has some benefits compared to electroluminescence and infrared approaches, namely in identifying mechanical flaws in the front glass. The Lamb waves (LW) method is an auspicious inspection approach among ultrasonic-based methods. This is primarily attributed to its quicker measurement speed than the standard ultrasonic c-scan. The LW method offers an advantage in terms of its ability to provide long-range coverage. The predominant approach in LW inquiry often centers on using fundamental modes within the low-frequency range. Nevertheless, the findings of this investigation demonstrate that the higher-order mode exhibits superior effectiveness for the specific objective of this research, as it displays a higher level of sensitivity towards cracks in the front glass of the module. The current study ultimately showcases the use of the LW scan. A damage indication threshold is determined by the fraction of energy spectral density (ESD) associated with the crack-sensitive mode. This technology effectively produces a comprehensive map of the designated area by comparing the ESD values at various measurement positions with a predetermined threshold. This map provides precise indications of the existence of areas that are affected by cracks. [ABSTRACT FROM AUTHOR]

• This study presents a 2-step milling process including dry and wet sequences. • It controls the contamination of TiO 2 and size of Re Si powders recycled from PV modules. • Micro- and nano-sized ReSi powders assessed as anode materials for Li-ion batteries. • Nano-sized ReSi improved Li-ion battery retention by 35.33% than micro-sized ReSi. Generally, economical recycling processes based on physical methods for recycling of photovoltaic (PV) modules include crushing or milling steps, accompanied by impurity contamination during the silicon (Si) recovery process of PV modules. Previous studies have deal with the contamination of metals, which can be treated relatively easily during further etching steps. However, the contamination of titanium dioxide (TiO 2) from the backsheet during the separation of modules has not been considered. In particular, subsequent chemical treatments is hard to remove the TiO 2 nanoparticles. This study presents a 2-step milling process including dry and wet sequences to control both the contamination and size of recovered Si (ReSi) powders directly recycled from PV modules. The proposed method achieved a tenfold reduction in TiO 2 concentration in ReSi, attained through the different sedimentation rates exhibited by Si and TiO 2 particles in the solvent during wet process. Moreover, the current methodology seamlessly establishes dry and wet milling conditions for minimizing the size of the ReSi powder by optimizing the ratio of milling media and milling time. The ReSi powders, of various particle sizes, were evaluated as anode materials for lithium-ion battery. In addition, the cycling performance and volume change of micro- and nano-sized ReSi were compared to validate the effect of 2-step milling. Nano-sized ReSi exhibited a 35.33% improvement in lithium-ion battery retention compared to micro-sized ReSi, along with a 57.67% decrease in volume expansion rate. [ABSTRACT FROM AUTHOR]

In the work, a dynamic model is proposed in Simulink, to model the behavior of photovoltaic modules and arrays. A novel methodology is proposed to obtain exactly the five parameters of the simple diode model, through the data provided by the manufacturer in the data sheet. The model proposes the calculation of the Volt-Ampere curve from environmental conditions, solar irradiance, ambient temperature and second-order effects, such as: the influence of temperature on the photocurrent generated and on the open circuit voltage, as well as the spectral and optical effects. The validity and accuracy of the proposed model is checked by comparing its results, with curves and experimental data from the manufacturer's data sheet. In addition, curves of the module are shown, allowing to evaluate its behavior taking in to account the optical and spectral effects.

Abstract India is implementing one of the world's largest solar PV program. For better performance assessment of large PV installations, module temperature plays an important role. Estimation of power generation in hot climatic countries like India can be improved by the use of appropriate module temperature correlation. The accuracy of module temperature correlations has been observed to be related with climatic conditions. In this work, different explicit and implicit correlations have been evaluated in different temperature ranges based on frequency of occurrence of three very different technology PV modules: amorphous silicon, hetero‐junction intrinsic thin layer, and multicrystalline silicon at Indian site. Results show that Faiman correlation is most efficacious for all technology PV modules under highest frequency of occurrence temperature range. It has been observed that accuracy of correlations decreases from low module temperature range toward high module temperature range for all technology PV modules, except in case of Faiman correlation. In case of multicrystalline silicon, which is most widely used technology, the variation in accuracy of correlations was highest. This frequency of occurrence‐based comparison of correlation's accuracy is efficient and beneficial for better performance assessment of PV systems, especially in Indian context due to its large solar mission.

Abstract Fault diagnosis and condition monitoring are important to increase the efficiency and reliability of photovoltaic modules. This paper reviews the challenges and limitations associated with fault diagnosis of solar modules. A thorough analysis of various faults responsible for failure of solar modules has been discussed. After reviewing relevant work, a monitoring tool is designed using thermography and artificial intelligent systems that allows the detection of various types of faults in PV modules and at the same time the designed tool aims to filter the nonsignificant anomalies. A neural network (NN) classifier is applied to the transfer characteristics (I‐V data) of the faulty PV module for the diagnosis which adapts multilayer perceptron (MLP) networks to identify the type and location of occurring faults. The Discrete wavelet transform (DWT) based signal processing technique is utilized in the feature extraction process to reduce the NN input size. The developed detection algorithm is adapted for 24/7 automated surveillance. For a given fault condition, the average fault detection time is observed to be

The development of a prospective simulation will serve as a guide in converting a diesel engine into 100% electric engine, this conversion will solve the problems facing nowadays in an energy crisis and greenhouse gas emission. The simulation derives the estimated power engine, the battery pack to be installed and the photovoltaic wattage for charging while transporting passengers and goods from Davao City to Samal Island Philippines. The results give an estimated power engine of 24.07 kW, 7.1 kA- hour battery bank and 64 kW of the photovoltaic module to charge the battery while on voyage. This study further helps the boat owner to find the suitable engine requirement in converting into the electric ferry. The prospective simulation is the stepping-stone in moving towards green energy source and electric mobilisation in the maritime sector.

Performance of 5 photovoltaic (PV) modules made of different technologies (monocrystalline silicon, polycrystalline silicon, amorphous silicon, copper indium selenide and heterojunction with intrinsic layer) is evaluated according to the short-term capacity evaluation method described in IEC TS 61724-2 standard. Measurements for the analysis are obtained from the data acquisition system developed by the Laboratory for Renewable Energy Sources at the Faculty of Electrical Engineering, Computer Science and Information Technology (FERIT) Osijek which is described in the paper. Results of the performance analysis according to the IEC TS 61724-2 standard indicate that the copper indium selenide PV module Solar Frontier SF150-S has the greatest performance, therefore it is the most suitable PV module for the micro-location of Osijek, Croatia with European humid continental climate. The lowest performance of all studied PV modules is achieved by polycrystalline silicon PV module Bisol BMU 250. Empirical analysis of the relations of various electrical and meteorological parameters is performed and dependencies are evaluated. In the last section, mathematical models of PV module efficiency in relation to the module temperature are derived based on empirical analysis of measurements.

The relevance. Changes in geopolitics and conjuncture of the world energy markets, impact more and more the world economy, forcing not only to improve energy technologies, but also to determine the priorities of the state in the field of energy policy. One of these priorities is to increase generation from new types of renewable energy sources and rapid development of appropriate technologies, which, in their turn, provide cheaper production. At the same time, it is known that it is possible to increase the reliability of the power system and at the same time to increase the production of electricity at the expense of distributed energy, the basis of which is micro-generation from solar power plants. In this regard, additional research is needed to adapt the existing methods of calculation of photovoltaic systems to their use in development and construction of low-power solar power plants. The relevance is also caused by the fact that it is necessary to create the most effective and inexpensive system for converting solar energy into electrical energy, which would meet any given technical requirements, would be reliable and easy to operate. The main aim of the research is to develop an effective photovoltaic system and design an inexpensive microelectric solar power plant with specified parameters and technical characteristics for further experimental studies. The methods. When calculating and studying the main operation modes and structural elements of photovoltaic systems, the authors have used the results of numerous scientific studies, including applied research, and available experience in the field of solar energy, which was obtained in the performance of some theoretical and experimental work. DipTrace and EasyEDA systems were used in development and modeling of electronic circuits. The results. The authors substantiate the expediency of application of more simple methods to determine the probable or actual exposure with the use of the software PVsyst, with an error of no more than 10 %. They developed the technology for experimental production of photovoltaic modules of given geometric dimensions and nominal power and the reliable control system for a biaxial solar tracker due to the actuators, which increases the efficiency of photovoltaic systems in the latitudes of Western and South-Western Siberia. A block diagram for controling a micro-power solar power plant and electronic circuits of the MPPT solar controller, DC-DC Converter, DC-AC inverter, and the main control unit based on the ATmega326 microcontroller were designed.

The photovoltaic (PV) module is a key technological advancement in renewable energy. When the PV modules fail, the overall generating efficiency will decrease, and the power system’s operation will be influenced. Hence, detecting the fault type when the PV modules are failing becomes important. This study proposed a hybrid algorithm by combining the symmetrized dot pattern (SDP) with a convolutional neural network (CNN) for PV module fault recognition. Three common faults are discussed, including poor welding, breakage, and bypass diode failure. Moreover, a fault-free module was added to the experiment for comparison. First, a high-frequency square signal was imported into the PV module, and the original signal was captured by the NI PXI-5105 high-speed data acquisition (DAQ) card for the hardware architecture. Afterward, the signal was imported into the SDP for calculation to create a snowflake image as the image feature for fault diagnosis. Finally, the PV module fault recognition was performed using CNN. There were 3200 test data records in this study, and 800 data records (200 data records of each fault) were used as test samples. The test results show that the recognition accuracy was as high as 99.88%. It is better than the traditional ENN algorithm, having an accuracy of 91.75%. Therefore, while capturing the fault signals effectively and displaying them in images, the proposed method accurately recognizes the PV modules’ fault types.

The paper considers the operation of an LED lighting system with a parallel power supply from photovoltaic modules and a power grid. Such systems are supposed to be widely applicable in premises with limited natural lighting, particularly agrosystems where artificial light of a certain spectrum is specifically required to ensure efficient plant growth. The paper presents the scheme of the developed LED lighting system, as well as an assembled prototype containing a single 36-watt lamp. The data of the experimental study are provided on the developed LED lighting system using the developed monitoring system. The experimental study demonstrates an efficient power take-off and the reliability of the proposed scheme to competently select the characteristics and circuit solutions for the converter of voltage from the PV module. The proposed LED system allows simplification of the PV system by eliminating circuits with an inverter and storage devices, hence significantly reducing the cost of the photovoltaic systems. Likewise, such a simplicity has a positive effect on PV system reliability, which benefits the cost as well.

Photovoltaic conversion is an optimal solution for the electrification of rural areas, especially deserts for the abundance of solar energy in these regions. In recent years, many studies have been carried out to maximize the energy productivity of a PV array system and increase its efficiency. However, the arid and semi-arid region is characterized by a climate whose parameters significantly influence the operation of PV installations. This paper presents an overview investigation of the major internal and external factors significantly affecting both the efficiency and the performance of solar cells and the power of PV systems. These factors include the type of PV material, solar radiation intensity received, cell temperature, parasitic resistances, cloud, and other shading effects, inverter efficiency, dust, module orientation, weather conditions, geographical location, and cable thickness. Simulation of a PV system has been carried out in MATLAB-SIMULINK to prove the effectiveness of the proposed modeling method. These simulation results are useful to predict the production of the PV module under real operating conditions.