
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12827-7
10.1016/j.heliyon.2024.e36796
e36796
Research Article
Examining the interplay of dust and defects: A comprehensive experimental analysis on the performance of photovoltaic modules
Azeem Ahsan a
Abbas Muhammad Farasat farasat.abbas@uspcase.nust.edu.pk
a⁎
Ahmed Naveed a
Kazmi Syed Ali Abbas a
Alharbi Talal b
Alharbi Abdulelah aly.Alharbi@qu.edu.sa
b⁎⁎
Ghoneim Sherif S.M. c
a US Pakistan Centre for Advanced Studies in Energy (USPCASE), National University of Sciences & Technology (NUST), H-12 Sector, Islamabad, 44000, Pakistan
b Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah, 52571, Qassim, Saudi Arabia
c Department of Electrical Engineering, College of Engineering, Taif University, P.O. BOX 11099, Taif, 21944, Saudi Arabia
⁎ Corresponding author. farasat.abbas@uspcase.nust.edu.pk
⁎⁎ Corresponding author. aly.Alharbi@qu.edu.sa
23 8 2024
15 9 2024
23 8 2024
10 17 e367966 5 2024
19 8 2024
22 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The performance of photovoltaic (PV) modules is greatly impacted by dust accumulation and defects appearing in photovoltaic (PV) modules. Existing studies primarily focus on the effect of dust on general photovoltaic performance, neglecting the interactions with pre-existing defects such as snail trails. These defects are known to degrade the efficiency of PV modules. However, their interaction with environmental factors like dust accumulation has not been extensively analyzed. This research comprehensively analyzes the impact of dust accumulation on the performance of PV modules affected by snail trails. Using an experimental setup under outdoor conditions, the study incorporates thermal imaging, current-voltage characteristic curve tracing (IV curve tracing), electroluminescence (EL) imaging, and chemical analysis of the accumulated dust, to evaluate the electrical and thermal parameters affecting PV module performance. The study focuses on three types of modules, clean serves as a reference module (PV-R), normal unclean (PV-N), and snail trail-affected unclean PV module (PV-S). Compared to the PV-R module, the study meticulously quantifies the effect of accumulated dust on key performance indicators such as output power, V, and I. The PV-N module exhibits reductions of 17.7 % in current, 3.91 % in voltage, and 18.15 % in power output. The PV-S module experienced a decrease of 7.4 % in current, 7.55 % in voltage, and 14.87 % in power output under the dust deposition density of 6.984 g/m^2 having a mean particle size of 2.2279 μm. The dust deposition reduced the transmittance of glass, which indicates a potentially adverse impact on the PV module's efficiency. The findings highlighted in the current work provide a significant understanding of the detrimental impacts of dust accumulation on defected photo voltaic modules, highlighting the need for regular maintenance and cleaning to ensure optimal performance.

Keywords

Solar energy
Photovoltaic
Snail trail
Dust effect
Thermal imaging(PV) defects
Soiling
Dust density
Degradation
==== Body
pmc Nomenclature

PV	Photo voltaic	
PV-R	Photo voltaic module Reference(clean)	
PV-N	Photo voltaic module normal (unclean)	
PV-S	Snail trail affected Photo voltaic module (unclean)	
FF	Fill factor	
EL	Electroluminescence imaging	
Voc	Open circuit voltage	
Isc	Short circuit current	
RE	Renewable energy	
Tamb	Ambient temperature	
NOCT	Nominal operating cell temperature	
STC	Standard testing conditions (1000W/m2, 25C, AM = 1.5)	

1 Introduction

Photovoltaic (PV) plants are becoming increasingly essential to meet the growing demand for clean energy. As the deployment of PV systems expands, various defects must be addressed to ensure optimal and reliable performance. The efficiency and performance of photovoltaic (PV) modules are critical to maximizing the potential of solar energy systems. Many uncontrollable factors and defects impact the photovoltaic power-generating system deployed in the natural environment. During operation, PV modules may have a range of defects, such as snail trails, microcracks, discoloration of the encapsulant, hotspots, and corrosion on busbars. However, various factors, such as dust accumulation and pre-existing defects, significantly impact the performance of the photovoltaic system [1]. These defects, except hotspots, may be detected by visual examination of photovoltaic installations. Apart from defects, surface contamination is the primary factor that significantly reduces the efficiency of solar modules [2]. The external factors including dust, wind, ambient temperature, and humidity have a significant effect on solar radiation and the photovoltaic module's efficiency [3]. Addressing these issues through innovative research and advanced technological solutions will be crucial in enhancing the efficiency and dependability of PV systems, thereby accelerating the transition to sustainable energy. Factors such as total radiation, projection ratio, derating factor, soiling loss index, and energy conversion efficiency are directly influenced by dust accumulation on PV modules [4]. Many studies have demonstrated that dust accumulation and shadow on photovoltaic modules raise the cell temperature of the surface [5]. Applying an anti-soiling coating to photovoltaic modules can minimize dust accumulation [6]. An 18 % increase in efficiency relative to manually cleaned photovoltaic modules is possible with the usage of hydrophilic nano-coated materials [7]. Another study claims a 13 % increase in output power generation even without regular cleaning while applying self-cleaning hydrophobic nanocoating in a semiarid location [8].

Particles with a diameter of less than 500 μm are defined as dust [9]. Fine particles have a diameter of less than 0.05 mm, medium particles range from 0.05 to 2 mm, and coarse particle varies from 2 to 57 mm respectively [10,11]. The size and density of dust particles deposited on the photovoltaic module's surface have a significant effect on their performance [12]. Fine particles compared to coarse particles, have a greater impact on the photovoltaic module's efficiency [13]. The presence of dust particles on the surface of the photovoltaic module can reduce the solar irradiance reaching the module surface and cause a decrease in the power output of the photovoltaic module [14]. Monocrystalline PV modules experience greater power losses compared to polycrystalline PV modules when dust with the same elemental composition is deposited on them [15]. As dust density on the surface of a photovoltaic module increases, the UV-generated current drops more significantly than the visible and infrared portions. Dust accumulation reduces current density, thereby decreasing the module's efficiency [16]. As per [17], accumulated dust of 4.6 g/m2 decreased the polycrystalline photovoltaic module's output power by 11.54 %. The photovoltaic output efficiency decreased up to 26 % as the dust deposition density reached 22 g/m2 [18]. When particle size increases a decrease in dust accumulation is observed [19]. Particles having a size greater than 10 μm can be effectively cleansed through a natural process facilitated by rainfall [20]. Dust deposition on a module causes the solar cell to heat up. PV modules experienced performance degradation as a result of industrial residue materials adhering to them [21]. The PV current encounters resistance in the impacted cell, significantly decreasing conversion efficiency and potentially leading to hotspot formation, which can damage the photovoltaic module over time.

An increase in temperature impacts the energy generation capacity of photovoltaic plants hence reducing the fill factor of PV plants. The Voc of the photovoltaic module is substantially influenced by cell temperature, and declines significantly as cell temperature rises, while the Isc increases just slightly. According to the literature, there is a 0.4 percent drop in Voc and a 0.09 percent increase in Isc for every 1 °C rise in the cell's temperature above the standard testing conditions [22]. Higher temperatures and increased dust deposition density in the summer cause PV modules to degrade faster than in other seasons [23]. The performance of a Solar Photovoltaic System (SPVS) can be significantly improved by implementing proper cooling techniques [24].

According to the International Energy Agency's (IEA) assessment, snail trails are categorized as a sort of discoloration [25]. Marc Kontges discovered a snail trail defect for the first time in 2004 [26]. Carbon dioxide from the atmosphere dissolved in moisture (H2O) interacts with the silver grid lines during outdoor exposure to the PV module, forming silver carbonate. Ag2Co3-silver carbonate combines with acetic acid CH3COOH generated during EVA degradation to form silver acetate which has a brownish tint named snail trails [27]. Cell metallization appears to be relevant only to produce silver carbonate and the permeation properties of the back sheet material are critical for all sorts of snail trails [28]. When snail trails occur on solar cells, they reduce photon penetration which affects the power of the PV module [29]. About 9.1 % of power degradation is induced by a reduction in absorption area, with no association with micro-cracks [30]. Snail trails might be due to environmental circumstances. However, some sort of pre-conditions are required to penetrate the structure of the cell. In general, a few factors are suspected of contributing to or hastening the creation of snail trails. They are classified into three types. Mechanical (micro-cracks), chemical (material's composition) [31], cell finger's chemical and physical properties [32] back sheet and encapsulates [33,34], and environmental, UV, and temperature [35]. The power loss due to snail trails may range from 9 % to 33 %, according to datasheet values. However, experts believed that the decline was mostly caused by micro-cracks, the presence of which was indicated by snail trails [36,37]. Micro cracks that follow snail tracks produce a 5 % drop, in comparison to initial parameters [38]. A study revealed that 96 % of snail trails are linked to micro-cracks [27]. Table 1 includes recent research and developments in this field.Table 1 Latest research and development in this field.

Table 1Reference	Location	Year	Main Findings	Limitations	
[39]		2024	Snail Trails can initiate different degradations.
Performance losses in modules with snail trails are attributed to various degradations observed with snail trails, including bubble formation and back sheet degradation.	The research does not delve into the long-term effects of snail trails on the performance and reliability of PV modules, which could provide valuable insights into the durability of the modules over time.	
[1]	Ghana	2023	Recently installed PV modules are more prone to visual defects than older ones.
Some modules with severe visual defects degrade less than those with minor or no defects.	The research primarily examined modules older than 5 years, potentially overlooking issues that may arise in newer installations.	
[40]	China	2024	The author investigated the erosion effects on output power and found that erosion rates of 25 m/s and 30 m/s can cause a decrease in output power of 9.82–16 % and 15.42–24.46 %, respectively.
Dust deposition with particle sizes ranging from 0.05 to 0.30 mm reduces the output power of PV systems by 17 %, the short circuit current by 13 %, and the voltage by 0.25 V.	The research primarily analyzed the effect of particle size on the performance parameters of photovoltaic modules, overlooking the influence of other characteristics of sand and dust particles, such as shape or composition, which could also play a role in module degradation and power output.	
[41]		2023	The author investigated the effect of ash and sand on PV module performance and found that the current losses due to ash deposition were greater compared to those caused by sand. Furthermore, using water for cleaning increased the efficiency of the PV modules by 3–4%.	The study mentions the increase in efficiency of photovoltaic modules when water is used for cleaning and cooling, but it lacks a comparative analysis with other cleaning methods or technologies.	
[42]	India	2023	The author investigated the impact of various types of dust on PV performance. The findings revealed that chalk buildup dust significantly affects PV performance compared to normal dust deposition.	The study primarily relied on MATLAB/Simulink models and experimental setups to analyze the effects of dust accumulation on PV systems, without considering other external factors that could influence the results, such as environmental conditions or panel orientation.	
[43]	India	2024	The author discovered that during periods of low deposition density, the dust has a homogeneous distribution. By following a proper cleaning schedule, losses were reduced by around 25 %. Additionally, fortnightly cleaning can lead to a 7 % reduction in losses compared to regular cleaning.	The cleaning methodologies studied in the research may not be universally applicable to all types of PV systems or locations, as the optimal cleaning interval fortnightly may vary based on factors such as dust concentration, weather patterns, and panel orientation.	

Few studies have been published in the literature emphasizing the significance of dust deposition on photovoltaic performance. Several studies investigated the most common sort of dust that causes performance reduction, neglecting the intricate interactions with pre-existing snail trails. Snail trails are known to degrade the efficiency of PV modules, but their combined effect with environmental factors such as dust has not been extensively analyzed. The primary aim of this research is to investigate the impact of dust accumulation on photovoltaic (PV) modules affected by snail trails, comparing their performance with that of clean modules. This study offers a thorough performance analysis by leveraging real-time operating data alongside a series of indoor and outdoor experiments. Three modules were tested: one with snail trails affecting its performance and two standard modules. By analyzing detailed dust characterization, correlating wind speed data, and assessing the output performance of the experimental setup, comprehensive insights into the interactions between environmental factors and PV efficiency can be obtained. It also undertakes a comparative investigation to explore how dust accumulation differently affects the performance of both snail trail-impacted and standard PV modules. To deepen the understanding of dust's impact, the collected dust samples underwent comprehensive analysis for elemental composition and particle size distribution using SEM-EDX. To evaluate performance impacts, an array of diagnostic tests was conducted, including EL imaging, I-V curve tracing, and thermal imaging. By integrating these aspects, the research seeks to provide a holistic understanding of the compounded effects of physical and environmental stressors on PV module efficiency and longevity. This research aims to enhance the efficiency and reliability of PV modules under varying outdoor conditions by understanding the mechanisms and effects of dust accumulation on snail trail-affected and standard PV modules. By offering a deeper understanding of these interactions, the study aims to advance the design and maintenance of more robust and efficient solar energy systems. Ultimately, this approach will contribute to optimizing maintenance strategies and improving the longevity and performance of PV systems across diverse climatic conditions. Moreover, this experimental approach is effective in providing valuable insights into the soiling losses.

2 Methodology

The methodological flowchart illustrating the methodology is shown in Fig. 1. The experimental setup was developed to examine the dust accumulation impact on the photovoltaic module's performance. The schematic diagram of the experimental setup is depicted in Fig. 2.Fig. 1 Methodological work's flowchart.

Fig. 1

Fig. 2 Schematic diagram of the experimental setup.

Fig. 2

The dust sample was analyzed for elemental composition and particle size analysis to investigate its effect further. The intended test rig was installed at USPCASE, NUST. The trial was carried out over two months, in September and October. The data is collected and evaluated on clear days, ensuring that the impact of dust on photovoltaic performance is not influenced by other factors such as sandstorms and rainfall. The results comprehensively understand how dust affects photovoltaic module output performance.

Fig. 3 depicts the experimental setup. The setup comprises three polycrystalline PV modules, a data acquisition system (DAS) coupled with a computer via a USB port, a data logger with K-type thermocouples for front and back sheet temperature readings, and acrylic sheets of tempered glass for measurements of deposited dust.Fig. 3 Experimental setup for study.

Fig. 3

The weather data that includes solar irradiance (w/m2), and ambient temperature (°C) were collected from the USPCASE weather station. A DAS consists of an SD card module, voltage, and current sensors that measure and store the output values of the modules. The schematic and circuit diagram of DAS is illustrated in Fig. 4.Fig. 4 (a) Schematic diagram of DAS (b) Circuit diagram of DAS.

Fig. 4

Three polycrystalline PV modules were investigated, two normal operating modules and one affected with a snail trail defect. The snail trail-affected module (c) has been in operation since August 2015. The other two modules (a) and (b), which serve as the study's reference module, have been in the field since 2016. The modules under investigation were dismounted from an On-Grid PV system operating in an industrial area. The latitude of Islamabad is 33.7°, hence the modules were set up at a tilt angle of 34.5° facing towards the south and natural dust accumulation was allowed. Table 2 illustrates the photovoltaic modules' electrical parameters that were utilized in the experiment.Table 2 Solar modules specifications.

Table 2Electrical Data	MODULE 1	MODULE 2	MODULE 3	
(at STC)	(PV-R)	(PV-N)	(PV-S)	
Maximum Power (Pmax)	260W	260W	250W	
Voltage at Maximum Power (Vmpp)	31.3V	31.3V	30.32V	
Current at Maximum Power (Imp)	8.31	8.31	8.25A	
Open Circuit Voltage (Voc)	38.2V	38.2V	37.39V	
Short Circuit Current (Isc)	9.02A	9.02A	8.8A	
Panel Efficiency	15.88 %	15.88 %	16.60 %	
Temperature Coefficient of Pmax	−0.43 %/K	−0.43 %/K	−0.423 %/°C	
Temperature Coefficient of Voc	−0.122V/K	−0.122V/K	−0.317 %/°C	
Temperature Coefficient of Isc	0.05 %/K	0.05 %/K	0.044 %/°C	
Cell Type	Polycrystalline Silicon	Polycrystalline Silicon	Polycrystalline Silicon	
Number of Cells	60	60	60	

For the measurement of dust accumulation, 5 acrylic sheets of tempered glass were employed. The area of each sheet is 0.0122 m2. The sheets were positioned at the same tilt angle as the photovoltaic modules in the experiment. Before the experiment, the weight of clean glass sheets was measured. The experiment involved weighing accumulated dust every 6 days. Afterward, the collected samples underwent evaluation for particle size, elemental analysis, and morphological structure. Dust deposition density was determined by dividing the mass of deposited dust by the surface area. The trial was carried out over two months, September, and October respectively.

The reduction in output power of the PV module due to dust accumulation is known as soiling loss. The soiling loss was calculated using Equation (1).(1) Soiling Loss = P clean – P unclean

Where P clean and P unclean are the output powers of clean and unclean PV modules respectively.

2.1 Visual inspection

The defects in PV modules can be identified using a simple and quick method known as visual inspection. Various defects identified during visual inspection are listed in the documents provided by IEC 61215 standards [44]. The present study comprises a visual inspection of all 3 modules included in the experiment to identify any potential faults. The few types of faults identified in the module were snail trails and discoloration of metallic grid lines.

2.2 EL imaging

The existence of corroded busbars, microcracks, and interrupted fingers in silicon cells is revealed by EL imaging. IEC standard 60904-13 technical specifications describe methods for EL imaging [45,46]. EL imaging was conducted before the experiment, to discover microcracks in modules. EL imaging of the modules was conducted in the darkroom. Potential was applied to the photovoltaic modules based on the values of Isc and Voc, specified in the datasheets of the modules. Images of the modules were captured.

2.3 IV curve tracing

The method employed for the evaluation of a photovoltaic (PV) module's performance or array, which is perfect for assessing all the potential operating points of PV modules or strings or arrays is known as IV curve tracing. IV curve tracer was used for testing by IEC standard 61215. Tests were conducted in outdoor conditions. On the first day of the experiment, the modules were cleaned with water. (Voc), (Isc), I-V curve of the module, fill factor, peak current (Ipeak), peak voltage (Vpeak), ambient temperature, module temperature, and solar irradiance were the parameters measured by the IV curve tracer.

2.4 Thermal imaging

Infrared thermography (IRT) is an excellent method to qualitatively characterize a PV module, notably in determining the type and exact position of the fault [47,48]. The IR thermal imaging of the modules was carried out by using a fluke thermal imaging camera that has a resolution of 640 × 480 and a temperature measurement range of up to 650 °C. Using thermocouples, the accuracy of infrared (IR) temperatures was validated. Fig. 3 depicts the data collection setup used to compare the IR images and thermocouples values.

2.5 Wind speed

The wind speed data was meticulously collected from a weather station installed near the experimentation site at NUST. The accompanying figure illustrates the average wind speed plot, meticulously charted throughout the 21-day experiment. During this period, the average wind speed was determined to be 2.74 m/s. Fig. 5 contains the plot of the daily average wind speed during the experiment.Fig. 5 Plot for average wind speed.

Fig. 5

2.6 Dust characterization

The surroundings around the experimental setup have a muddy and less populated environment. The dry mud, moisture, and wind turn fine particles easily get carried and spread in the surrounding environment. Human activities like construction or use of unpaved roads by vehicles can create and stir up dust particles in the area. The dust particles have been collected from all the panels and analyzed to check their elemental and structural properties. Elemental and morphological analysis of the dust sample has been performed by scanning electron microscopy (JSM-6490A) embedded with energy dispersive spectroscopy (EDS). The sample was coated with platinum film with the help of sputter coating to exclude charges that could affect the image resolution. SEM images have been further analyzed by ImageJ software to predict the particle size distribution of the dust collected from the panels.

2.7 Uncertainty analysis

The uncertainty of the sensors used for data acquisition is presented in the table. Equation (2) indicates uncertainty and measurement error, where V, I, and T represent the values of voltage, current, and temperature of PV modules, respectively [49]. Ѡ represents the uncertainty of the data acquisition system, which is calculated as 3.01 %. Table 3 contains the uncertainty of sensors used in the experiment.(2) Ѡ=(ѠvV)2+(ѠII)2+(ѠTT)2

Table 3 Uncertainty of sensors.

Table 3Sensor	Uncertainty range (%)	
Voltage sensor	0.5–1.0 %	
Current sensor	0.5–2.0 %	
Temperature Datalogger	0.2–1.5 %	

3 Results and discussions

3.1 Dust characterization

Total dust deposition, at the end of 24 days of the experiment was 6.984 g/m^2, this resulted in an average daily dust accumulation of 0.291 g/m^2. The dust density varied over different periods: for the first 6 days (days one to six), it was 1.6908 g/m^2 2, followed by 1.078 g/m^2 from the seventh to twelfth day of the study, 2.778 g/m^2for days thirteen to eighteen, and 1.438 g/m^2for days nineteen to twenty-four. The corresponding average daily dust densities for these periods were 0.282 g/m^2 0.180 g/m^2, 0.462 g/m^2, and 0.240 g/m^2, respectively. Fig. 6 contains the plot of overall accumulated dust densities.Fig. 6 Deposited dust density.

Fig. 6

Dust samples collected from the panels during the experiment contained carbon, oxygen, silica, aluminum, and calcium as the main elements but other elements with less weight % are also observed in the spectrum. Table 4 contains the EDS spectra for all elements.Table 4 Elemental analysis of dust.

Table 4ELEMENTS	DUST ACCUMULATED DURING THE EXPERIMENT	
WEIGHT %	ATOMIC %	
Carbon (C)	10.4	16.8	
Oxygen (O)	48.3	58.7	
Magnesium (Mg)	1.5	5.1	
Silica (Si)	13.8	9.5	
Titanium (Ti)	0.6	1.0	
Aluminum (Al)	7.1	5.1	
Potassium (K)	2.5	0.21	
Calcium (Ca)	11.9	1.14	
Iron (Fe)	4.1	1.0	

The examination of dust samples taken from panels at sites using scanning electron microscopy (SEM) uncovered noticeable variations in the shape and structure of the particles.

Fig. 7 contains SEM Images of accumulated dust. The dust particles collected from the panels at the experimental site have a distinct porous and rounded form. This shape suggests that the dust in this area is probably finer and less harsh. The porosity of these particles could imply the existence of matter or lighter abrasive substances, which might have a gentler effect, on the surfaces of the solar panels. Fig. 8 contains the EDX results of the dust sample.Fig. 7 SEM images of accumulated dust.

Fig. 7

Fig. 8 EDX results of accumulated dust.

Fig. 8

Fig. 9 depicts the particle size distribution of the desired dust sample collected from the panel, with particle size set out along the x-axis (μm) and the relative frequency of occurrence expressed as a percentage along the y-axis. The size of distributed dust particles is presented in discrete intervals, with the height of each bar corresponding to the count percentage of particles falling within that specific size range.Fig. 9 Particle size distribution of accumulated dust.

Fig. 9

Additionally, a red curve expressing a normal distribution of microparticles has been superimposed, highlighting the overall trend for the particle size distribution. The mean particle size is reported as 2.2279 μm, with a standard deviation (SD) of 0.2397 μm, indicating a relatively narrow size distribution. These parameters suggest that the majority of particles cluster around the mean size, with fewer particles at the extremities of the size spectrum.(see. Table 6)

3.2 IV curve tracing

The modules have been operating in the field since 2015. Fig. 10 includes the actual and normalized curves of the modules. The table presents data derived from the IV curves of the PV modules. The presence of snail trails has a detrimental effect on the output of the PV module, resulting in hotspots and cell discoloration. Fig. 10 illustrates both the actual and normalized curves of the modules. The IV curve for the clean module PV-R indicates a power of 190.6W. In contrast, the IV curve for another clean module PV-N with dust accumulation shows a slightly higher power of 190.7W. Notably, the IV curve for the PV-S module affected by snail trails shows a significantly reduced power of 104.8W. Upon normalization of the curves according to STC the IV curves of modules show 250W, 251.5W, and 143W of power respectively. IV curve tracing of the snail trail affected module PV-S was also performed in 2021. The IV curve tracing in 2022 revealed that the module underwent a performance degradation of 7.14 % than 2021 as normalized data of IV curve tracing of the snail trail affected module is listed in Table 5.Fig. 10 IV curves: (a) PV-S (b) PV-R (c) PV-N.

Fig. 10

Tables 5 IV curve tracing data of module affected by snail trail (PV-S).

Tables 5Test Parameters	Normalize Curve Data at STC (2021)	Measured Data in 2022	Normalize Curve Data at STC (2022)	Manufacturer Data	
Solar irradiance (W/m2)	1000 W/m2	914 W/m2	1000 W/m2	1000 W/m2	
Temperature (°C)	25 °C	34.7 °C	25 °C	25 °C	
Voc (V)	36.03 V	31.585 V	36.065 V	38.26 V	
Isc (A)	7.86 A	7.099 A	8.100 A	8.39 A	
Vmax (V)	28.01 V	24.755 V	29.095 V	31.22 V	
Imax (A)	5.50 A	4.232 A	4.917 A	8.01 A	
Pmax (W)	154 W	104.8 W	143.0 W	250 W	
Fill factor	54.40	46.7	49.0	77.90	
Efficiency	–	–	–	15.58	

Table 6 Comparison of studies from the literature.

Table 6Reference	Efficiency loss	Year	Region	Findings	
[50]	25.42 %	2023	Pakistan	The study was conducted in two different regions in Pakistan. The authors found that in Islamabad, a dust density of 6.33 g/m^2 caused a 15.08 % reduction in efficiency, while a density of 10.254 g/m^2 resulted in a 25.42 % reduction. The accumulated dust also led to an increase in temperature, which further decreased the PV efficiency.	
[51]	80 %	2020	Iraq	The authors found that dust accumulation can cause a reduction in efficiency ranging from 1 % to 80 %, depending on various operating conditions and locations.	
[52]	6 %	2020	Iran	The authors discovered that a dust deposition of 10 g/m^2 can cause the temperature of PV modules to increase by 6 %. The impact of dust accumulation is more significant on mono-crystalline PV modules compared to poly-crystalline PV modules.	
[53]	21.57 %	2021	Mauritania	The authors found that the conversion efficiency of PV modules decreased by 21.57 % due to accumulated dust.	
[54]	40 %	2020	Iraq	The authors discovered that the output of PV modules decreases by 35–40 % during two months of outdoor exposure without cleaning.	
[55]	45.6 %	2021	Oman	The authors found that the efficiency of PV modules decreased by 9.5 %, 18.2 %, 31.3 %, and 45.6 % over cleaning cycles of 29, 32, 72, and 98 days, respectively.	
[56]	0.7 %	2018	Djibouti	The study found that for every one-degree increase in temperature above 25 °C, there is a 0.7 % decrease in performance.	
[57]	40 %	2019	Bahrain	The study found a 40 % reduction in capacity due to the accumulation of dust, which ranged from 5 to 12 g/m^2.	

3.3 Thermal imaging

Thermal imaging of all three modules was performed as shown in Fig. 11. The normal modules didn't show any hot spots, while module 3 affected by snail trails had 1 cell having a hot spot when the image was observed. When the image was exposed to a more infrared zone, a higher temperature was observed for one other cell as compared to another. The cells affected with snail trails showed higher temperatures than other normal cells which means that snail trails increase the temperature of the cell. Those normal cells that are not affected by snail trails didn't show any hot spots. The discoloration has also started on the cell showing a hot spot having all the adjacent cells from four sides affected with snail trails. This means that snail trails cause temperature increases and due to an increase in temperature discoloration has started on the cell showing hot spots [58].Fig. 11 Thermal Imaging of (PV-S) module from low to high infrared appearance.

Fig. 11

3.4 EL imaging

EL imaging of all three modules was done. Modules with no sign of snail trails didn't show any sign of micro-cracks or dark spots in the EL imaging as shown in Fig. 12.Fig. 12 (a) EL image of (PV-R) module (b) EL Image of (PV-N) module.

Fig. 12

While the EL image of the module affected by snail trails shows 14 cells having dark spots or micro-cracks. The dark spots or darker areas in the cells in the EL image of the module indicate that no or less current is passing through these cells [59,60] The EL imaging of the snail trail affected module was also done, back in 2021, there is no difference in both EL images. The number of cells having microcracks is the same. But discoloration has started on a cell having all the adjacent four cells from four sides having snail trails on them and this cell is indicated as a hotspot by thermal imaging of the module. Thus microcracks are the reason for snail trails as microcracks were observed only on those cells having snail trails, and those cells affected with snail trails have higher temperatures than other cells of the module, which means microcracks cause temperature increase [58]. As authors [58], and [61] indicated microcracks are the main cause of hot spots. There was no hotspot, and no signs of discoloration were present when this module was tested back in 2021. The only cell showing discoloration meant that a lower current was passing through that cell as shown in El imaging, increasing the overall temperature of the cell and resulting in discoloration. Fig. 13 (a) includes the EL images of the snail trail-affected module. There is no increase in the number of snail trail-affected cells, but discoloration has appeared on 1 cell, as shown in Fig. 13 (b).Fig. 13 (a) EL image of (PV-S) module (b) Discoloration on (PV-S) module.

Fig. 13

3.5 Electrical parameters

The primary factor influencing the performance degradation rate of a PV module is the rate at which dust accumulates on its surface. The entire experiment monitors the day-to-day operation of both clean and dirty modules. Clear days with similar weather conditions and power output were chosen for data analysis. Additionally, the impact of clouds or low irradiance on the output powers of clean and dirty modules was assessed by simulating conditions resembling an overcast day without rain. Parameters such as dust density, daily output power, output power loss, front and rear sheets' temperatures of PV modules, and ambient temperature were considered to assess the effect of dust on the output of the PV modules.

3.5.1 Comparison of voltage variation between snail trail affected and normal PV modules

The effect of temperature variation on voltage is more evident in comparison to its effect on current [62]. Soiling increases the temperature of the module because dust particles absorb solar radiation, leading to a rise in temperature. When the temperature of the module increases from its nominal value, it affects the module's output voltage.

Therefore, an experiment was conducted to observe voltage variations in three scenarios: a cleaned PV module (normal), an uncleaned PV module (normal), and a snail trail-affected unclean PV module, all set at a tilt angle of 34.5°. The daily average percentage difference plots for the voltage of PV-R vs. PV-N modules and PV-R vs. PV-S modules are shown in Fig. 14. Pointing to Fig. 14, the % daily difference in voltage between clean and unclean modules was small but consistent. However, as more dust accumulated, the difference continued to keep increasing. After 24 days of experimentation, it was observed that a voltage loss of 3.91 % for the PV-N module and 7.545 % for the PV-S module occurred as compared to the clean module. However, the voltage loss in the PV-S module was higher than that in the PV-N module. This elevated voltage loss in the PV-R module can be attributed to the high-temperature rise within the defective cells and the presence of snail trails as the daily average temperature of the back sheet of the PV-R module was higher than that of the PV-N module. Intriguingly, the defective cells during the 24-day experiment potentially exacerbated the voltage loss in the defective module. The PV-R module was experiencing a voltage loss of 36.05 % at the start of the experiment due to the higher temperature of the cells because of snail trails presence and the accumulated dust also increased the temperature of the module which led to more voltage drop in the PV-S module. The voltage loss for the PV-S module at the end of the experiment was 43.60 %.Fig. 14 Unveiling the daily voltage average percentage difference.

Fig. 14

Two consecutive days, 17 and 18 had approximately the same environmental conditions. The difference in temperature of modules increased due to soiling and that increase in temperature led to a voltage drop of 0.536 % and 0.167 % for PV-S and PV-N modules respectively. The voltage drops of the snail trail affected the PV-S module for that day was 0.369 % higher than the PV-N module. The same accumulated dust density refers to the drop in voltage to the higher temperature of the defective module.

These findings highlight the critical role of temperature and defects in affecting the voltage output of solar PV modules. Defects and high temperatures lead to higher voltage losses.

3.5.2 Comparison of current variation between snail trail affected and normal PV modules

The current output of a solar PV module is significantly affected by the amount of solar irradiance it receives on its front glass. Any factor that reduces the incoming irradiance can lead to a decrease in current production [62]. Among these factors, soiling is a major concern that can negatively impact PV modules' performance [63]. The daily average percentage difference plots for the current of PV-R vs PV-N and PV-R vs PV-S modules are shown in Fig. 15. The snail trails affected the PV-S module produced 35.6 % less current than the PV-R module while having a clean front surface on day 1 of the experiment. This current loss in the PV-S module was primarily attributed to the presence of several hotspots and snail trails. The higher temperature than the nominal temperature affects the current of the PV module, as it causes a slight increase in the current of the module [22].Fig. 15 Unveiling the daily current's average percentage difference.

Fig. 15

The percentage difference in the average daily current of the modules at the start of the experiment for PV-N and PV-S modules is 0 and 35.6 % respectively as compared to PV-R. The percentage difference for the PV-S module increases slowly as compared to the PV-N module, as the defective module is already experiencing a current loss of 35.6 %. At the end of the experiment, the % loss in average daily current for the PV-S module was less than the PV-N module under the same density of deposited dust. The lower daily % current loss for the PV-S than the PV-N module shows that the snail trail-affected unclean module has less effect of dust accumulation as compared to the PV-N. The reduced losses in the PV-S module were due to the presence of existing losses caused by the snail trail. The PV-N module undergoes an average current loss of 10.73 % more than that of the PV-S module showing that the PV-S module performs better in terms of current output than that of the normal uncleaned module (PV-N). 2 adjacent days, 17 and 18 in the experiment with approximately the same solar irradiance show that the difference in % current loss from the previous day due to soiling Two consecutive days, the 17th and 18th, in the experiment with approximately the same solar irradiance, show that the difference in percentage current loss from the previous day is due to soiling. Same for days 19 and 20 of the experiment where % losses on day 20 for PV-N and PV-S modules were 0.8322 % and 0.3509 % respectively, compared to day 19. This indicates a higher effect of dust accumulation on PV-N modules while having the same amount of accumulated dust density under the same operating conditions.

After 24 days of experimentation, the current loss in the PV-S module increased from 35.6 % to 42.947 %, while the current loss due to soiling on the same module was only 7.4 %. Surprisingly, the PV-N module exhibited a current loss of 17.7 %, indicating that its performance degradation due to soiling was greater than that of the PV-S module under the same operating conditions. Another analysis suggests that the cells of the PV-S module already had lower output current due to the presence of microcracks [64].

3.5.3 Comparison of power variation between snail trail affected and normal solar PV module

Solar radiation significantly influences the output power of PV modules. In this experiment, the power generation of solar PV modules was observed, while considering various factors contributing to power loss. Specifically, the impact of ambient temperature fluctuations and the presence of soiling on the power output of solar PV modules was investigated. Soiling can lead to substantial efficiency loss in PV modules [64]. To illustrate how dust affects the ability of PV modules to generate electricity, the output power of clean and dirty modules was compared. Initially, all three modules had pristine front surfaces, resulting in no differences in power output due to soiling on the first day of the experiment. However, as dust deposition was allowed on PV-N and PV-S modules, the difference in power output began to increase. Each morning, the reference module PV-R was cleaned, serving as the standard against which the outputs of modules PV-N and PV-S were measured. Over 24 days, a significant difference in power loss was observed. The daily average percentage difference plots for the output powers of PV-R vs. PV-N modules and PV-R vs. PV-S modules are depicted in Fig. 16(a). Power losses of the PV-N module were higher due to higher current losses as compared to the PV-S module, The PV-N module experienced an 18.15 % loss in power output, while the PV-S module depicted a decrease of 14.87 % in power output. However, the notable finding was that the PV-S module exhibited a substantial power loss of 42.3 % on its first day of the experiment, which escalated to a staggering 57.17 % power loss after 24 days of soiling. On the first day of the experiment, there was no difference in power between the modules in terms of percentage. The following day, it was 0.3281 % for PV-N and 0.3411 % for PV-S modules. For the second day, the power losses for the PV-N module were 0.3612 %, and for the PV-S module were 0.3823 %, as more dust built up and diminished its power, it continued to rise. But during the last days when dust density was high, the dust accumulation effect on the PV-S was less than that of the PV-N module as shown in Fig. 16 (a). The % power losses during 19–24 days for the PV-N module were 0.94, 1.12, 1.14, 1.24, 1.35, and 1.426 %, and for the PV-S module 0.77, 0.791, 0.796, 0.7999, 0.812 % from the previous day as shown in Fig. 16 (a). The PV-S module shows fewer losses than the PV-N module under the same deposited dust density. Irradiance was low on day 12, the day of the experiment with clouds in the sky. On that day, the impact of dust accumulation was minimal. At that time, there wasn't much of a difference in output power between dusty and clean modules. There was a difference of 4.12 % between the power of PV-R and PV-N and a difference of 42.24 % between the PV-R and PV-S module's power. This happened because clean modules suffered more recombination losses at that time than dusty modules [65]. Fig. 16(b) depicts the comparison plot of the three modules' power on day 12.Fig. 16 (a) Daily performance dynamics with average percentage differences in power for PV-R vs PV-N and PV-R vs PV-S (b) Output power of all PV modules on twelfth day.

Fig. 16

Fig. 16(b) illustrates the disparity in performance between the two unclean modules. The figures indicate that, when subjected to an identical density of accumulated dust, the power reduction in the PV-N module is greater compared to the PV-S module. By the experiment's conclusion, the accumulated dust density reached 6.98 g/m^2, with a daily accumulation rate of 0.291 g/m^2. This resulted in a power loss of 18.15 % for the standard unclean PV-N module and 14.87 % for the affected PV-S module, showing that the snail trail-affected module performed well while having the same amount of accumulated dust.

3.6 Comparison of temperature between snail trail affected and normal PV modules

The efficiency degradation of a solar PV module is directly affected by an increase in temperature, with a decrease in output observed once the temperature surpasses 25 °C [66]. Furthermore, the accumulation of soil on the module's front surface contributes to elevated temperatures both on the front surface and within the solar cells. The temperatures of the front and back surfaces of the modules were monitored. On the first day of the experiment, a front surface temperature difference of 1.83 °C was observed between the normal (cleaned and uncleaned) PV modules and the PV-S module, indicating higher temperatures due to snail trails. This temperature difference continued to grow as dust accumulated on the PV modules. After 24 days of soiling, the average front surface temperature of the PV-N module was 1.10 °C higher than that of the PV-R module. Meanwhile, the average front surface temperature of the PV-S module after 24 days was 4.35 °C, resulting in an average front surface temperature difference of 2.52 °C from the PV-R module. The average front surface temperature difference between the PV-N module and the PV-S module was 3.24 °C which means the unclean defective module has a temperature difference of 1.41 °C from the unclean module. This shows that the module affected by snail trails has a higher daily average temperature than a PV-N module due to soiling. The difference in the temperature of the front and back sheets of the unclean modules kept on increasing as more dust was accumulating on them. The front surface temperature of the PV-S module increased by 2.52 °C from the reference clean.

PV-R module, primarily due to soiling. In contrast, the front surface temperature of the PV-N module increased by only 1.10 °C from the reference clean module (PV-R). Fig. 17 contains the temperature plot for front sheets of (a) PV-R vs PV-N (b) PV-R vs PV-S (c) the daily average temperature difference of front sheets of PV-R vs PV-N and PV-R vs PV-S modules. On the first day of the experiment, there was an average temperature difference of 12.47 °C between the back sheets of the normal PV modules and the PV-S module. After 24 days of the experiment. The average back surface temperature of the PV-N module was 1.49 °C higher than that of the PV-R module. In contrast, there was a substantial difference in the average back surface temperature between the PV-R and PV-S modules, reaching 19.61 °C. Notably, a temperature difference of 7.14 °C in the back sheet of the PV-S module was recorded at the end of the 24-day experiment compared to its initial measurement. Fig. 18 illustrates the temperature plots for the back sheets of (a) PV-R vs. PV-N, (b) PV-R vs. PV-S, and (c) the daily average temperature difference of back sheets between PV-R vs PV-N and PV-R vs PV-S modules. The PV-S module experienced a temperature increase of 5.65 °C compared to the PV-N module, despite having the same dust deposition density. These findings highlight that the front and back sheet temperature increase of the PV-S module was nearly 2.28 and 4.79 times higher than that of the PV-N module.Fig. 17 Front Sheets Temperature difference of modules (a) (PV-R) vs (PV-N) (b) (PV-R) vs (PV-S) (c) Exploring the Percentage Temperature Differences Between (PV-R) vs (PV-N) and (PV-R) vs (PV-S).

Fig. 17

Fig. 18 Back Sheets Temperature Difference of Modules (a) (PV-R) vs (PV-S) (b) (PV-R) vs (PV-N) (c) Exploring the Percentage Temperature Differences Between (PV-R) vs (PV-N) and (PV-R) vs (PV-S).

Fig. 18

The PV-N module exhibits a temperature difference of 1.49 °C compared to the clean module. This temperature variance between the PV-R and PV-N modules arises from dust deposition, given that they operated under identical conditions. Thus, it can be concluded that a 24-day dust deposition, with a daily average dust deposition density of 0.291 g/m^2, has the potential to elevate the back sheet temperature of the module by 1.49 °C.

The deposition of dust not only raises the temperature of the back sheet but also affects the temperature of the front glass of the PV modules. In the case of the PV-N module, a 24-day dust deposition causes a temperature increase of 1.10 °C for the front sheet and 1.49 °C for the back sheet. This suggests that accumulated dust has a more pronounced impact on the temperature of the module's back sheet compared to the front glass. The results indicate that without proper cleaning of the snail trail-affected module, both defects and average front and back surface temperatures increase. A higher number of defects in the solar PV module contributes to greater electrical and thermal losses. Overall, soiling negatively affects the performance of the solar PV module.

4 Conclusion

An experimental study has provided valuable insights into the effects of dust accumulation and snail trail defects of PV modules. The observation revealed a consistent count of snail trail-affected cells over the three years. Nevertheless, the occurrence of hotspots and discoloration in a snail trail-affected cell, surrounded by adjacent cells on all four sides also affected by snail trails, indicated a gradual localized degradation, underscoring the need for regular monitoring and maintenance of PV modules to prevent long-term efficiency losses.• IV curve tracing indicated that the occurrence of hot spots and cell discoloration caused a drop of 7.14 % in the performance of the PV-S module as compared to the previous year.

• A 6.984g/m2 of deposited dust having a mean particle size of 2.2279 μm, significantly reduced the output power of unclean modules. Specifically, a reduction of 18.15 % and 14.87 % in the power output of the PV-N and PV-S modules respectively.

• Dust deposition differently affects the current and voltage parameters of PV modules. The PV-N module experienced a loss of 17.7 % in current, while the PV-S module experienced a loss of 7.4 %.

• The % voltage losses for the PV-N module was 3.91 % and for the PV-S module voltage losses were 7.545 %. A significant rise in the temperature of both the front and back sheets of the modules occurred due to dust deposition.

• The front and back sheet temperature of the PV-S module increased 2.29 and 4.79 times the temperature of the PV-N module, showing that the deposition of dust not only reduces the electrical performance but also contributes to thermal stress.

• The chemical analysis of the dust sample revealed that it contains oxygen, silicon, carbon, aluminum, iron, potassium, and titanium.

The findings suggest that regular cleaning and maintenance are necessary for sustaining the performance of PV installations. Future research should focus on the development of more resilient PV modules and the importance of efficient cleaning strategies, especially in dust-prone environments. Additionally, quantifying the long-term impacts of these defects and dust accumulation on the overall lifespan and efficiency of PV modules will be crucial. Research into advanced sensor technology for real-time monitoring and predictive maintenance algorithms could further enhance the reliability and performance of PV systems. Conducting long-term studies to quantify the cumulative impact of defects and dust accumulation on the lifespan and efficiency of PV modules. This will provide a more comprehensive understanding of the degradation mechanisms and help in formulating better maintenance practices.

Data availability statement

The data associated with our study has not been deposited into a public repository. The data will be made available on request.

CRediT authorship contribution statement

Ahsan Azeem: Writing – original draft, Visualization, Software, Methodology, Investigation. Muhammad Farasat Abbas: Writing – review & editing, Visualization, Validation, Supervision, Resources, Project administration, Conceptualization. Naveed Ahmed: Writing – review & editing, Validation, Supervision, Project administration, Methodology, Investigation, Data curation, Conceptualization. Syed Ali Abbas Kazmi: Writing – review & editing, Validation. Talal Alharbi: Writing – review & editing, Visualization, Validation, Investigation. Abdulelah Alharbi: Writing – review & editing, Supervision, Resources, Investigation, Funding acquisition, Formal analysis. Sherif S.M. Ghoneim: Writing – review & editing, Validation, Resources, Investigation, Formal analysis.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The Researchers would like to thank the Deanship of Graduate Studies and Scientific Research at 10.13039/501100007414 Qassim University for financial support (QU-APC-2024-9/1 ).
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