INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 113
www.rsisinternational.org
Review on Performance improvement of Solar PV Panels with
alignment of different Environmental Parameters
Sanjib Hazarika
1
, Sandip Bordoloi
2
1,2
Girijananda Chowdhury University, Guwahati, Assam
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.1502000009
Received Received: 13 February 2026; Accepted: 18 February 2026; Published: 25 February 2026
ABSTRACT
This study examines the critical environmental parameters that influence photovoltaic performance, including
solar irradiance, temperature, wind speed, humidity, and dust deposition, to elucidate the complex links between
ambient conditions and panel efficiency Specifically, research indicates that efficiency is directly proportional
to solar irradiance and wind speed and is inversely proportional to temperature, humidity, and dew point
temperature. To quantify these relationships, linear regression analysis is often employed to model efficiency as
a dependent variable against independent meteorological factors, thereby allowing for the prediction of power
generation under varying weather scenarios. Field studies have demonstrated that energy losses ranging from
21.4% to 37.5% can occur due to the absence of rainfall over extended periods, highlighting the severity of
environmental stressors on photovoltaic systems. Furthermore, specific environmental parameters such as wind
velocity, ambient temperature, and dust concentration have been shown to influence power output continuously,
with lower humidity levels between 69% and 75% correlating with increased power generation.
Keywords: Energy Loss, Performance loss, Dust impact
Parameters influencing Solar PV
The growing global demand for renewable energy has positioned photovoltaic panels as a primary technology
for solar energy harvesting, yet their operational efficiency remains inextricably linked to prevailing
environmental conditions [1]. While solar irradiance serves as the fundamental driver of energy generation,
ambient variables such as temperature, humidity, wind speed, and dust deposition introduce complex non-linear
effects that can significantly alter the actual power output relative to theoretical performance
[1], [2].
Conversely, the accumulation of airborne dust and other atmospheric contaminants presents a significant
physical barrier to energy conversion, as these particles obstruct sunlight from reaching the photovoltaic cells
and can reduce power output to as low as 50% of maximum levels without regular maintenance[1]. Beyond
physical obstruction, high relative humidity contributes to efficiency losses by promoting the formation of water
droplets and sticky dust layers that scatter incident radiation and prevent direct sunlight from reaching the solar
cells[1]. This phenomenon is further exacerbated by elevated dew point temperatures, which indicate higher
atmospheric moisture levels and have been statistically correlated with a decline in photovoltaic efficiency
through a negative linear relationship
[3].
Background on Solar Photovoltaic Technology
Solar photovoltaic technology functions on the fundamental principle of converting incident sunlight directly
into electrical energy through the photovoltaic effect; this process relies on semiconductor materials to absorb
photons and dislodge electrons, creating a flow of current.
However, the exposure of these systems to the open atmosphere subjects them to various environmental
phenomena that can induce performance degradation, system deterioration, and energy loss, particularly in
regions characterized by high humidity, frequent rainfall, and significant temperature swings
[4].
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 114
www.rsisinternational.org
Principles of Photovoltaic Conversion
The photovoltaic effect occurs when photons with sufficient energy strike the semiconductor material, typically
silicon, causing electrons to be excited from the valence band to the conduction band and thereby generating
electron-hole pairs that are separated by the internal electric field of the p-n junction to produce direct current
electricity
[5].
External circuitry subsequently harnesses this generated voltage to power electrical loads, though the magnitude
of the output is highly sensitive to the spectral distribution of the incident light and the operating temperature of
the semiconductor material
[6], [7].
As the operating temperature rises, the semiconductor's bandgap narrows slightly, which increases the intrinsic
carrier concentration and leads to a reduction in the open-circuit voltage, ultimately diminishing the overall
conversion efficiency of the photovoltaic device
[8], [9].
Types of Solar Panels
The theoretical performance of photovoltaic systems is governed by the Standard Test Conditions, which specify
an irradiance of 1000 W/m², a cell temperature of 25°C, and an air mass of 1.5, yet real-world deployment
exposes modules to a dynamic range of meteorological variables that deviate significantly from these idealized
parameters.
These environmental stressors include ambient temperature fluctuations, solar irradiance variability, wind
velocity, humidity levels, and particulate accumulation, all of which interact to modify the actual energy yield
compared to laboratory-rated capacities
[10], [11].
This discrepancy arises because the remaining incident solar radiation that is not converted into electricity is
transformed into heat, which raises the temperature of the PV module and reduces its efficiency
[9].
High relative humidity further compounds these thermal losses by introducing moisture that can corrode
electrical contacts and promote the adhesion of dust particles, which scatter incoming light and reduce the
effective irradiance reaching the active cell area [3], [12]. Additionally, the angle of incidence of solar irradiation
and the intensity of the incident light are critical determinants of the maximum power value obtainable from a
solar panel
[13].
The spectral content of the sunlight also plays a crucial role, as the semiconductor material's bandgap energy
determines the specific range of photon wavelengths that can be effectively absorbed to generate electron-hole
pairs
[14]. Elevated temperatures alter the dynamics of charge carriers, hindering their contribution to electrical
current generation [14].
Environmental Parameters Affecting Solar Panel Efficiency
Temperature Effects exerts a profound influence on the electrical characteristics of photovoltaic modules, as the
performance of semiconductor materials is intrinsically sensitive to thermal variations that alter the efficiency
of the photovoltaic conversion process
[15].
Specifically, as the cell temperature increases beyond the standard test conditions, the open-circuit voltage
decreases at a rate of approximately 0.3% to 0.5% per degree Celsius
[16], resulting in a net reduction of power
output despite a marginal increase in short-circuit current[15]. Consequently, for most crystalline silicon
technologies, the maximum power output typically declines at a rate of 0.4% to 0.5% per degree Celsius increase
in cell temperature, creating a significant performance gap in hot climates where module temperatures frequently
exceed 25°C. This thermal sensitivity necessitates careful consideration of installation methods and site selection
to minimize heat accumulation and ensure that the operating temperature remains as close as possible to standard
test conditions for optimal energy yield.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 115
www.rsisinternational.org
Electrical Losses.
Electrical losses within photovoltaic systems arise primarily from internal resistances, including series resistance
in the cell's bulk material and contacts as well as shunt resistance across the p-n junction, all of which impede
the flow of generated current and reduce the fill factor.
These resistive losses are further compounded by the temperature dependence of the semiconductor material,
where increased thermal energy leads to higher intrinsic carrier concentration and a reduction in the open-circuit
voltage, thereby diminishing the overall power output
[17], [18].
The temperature coefficient quantifies this reduction in voltage, which typically indicates a power loss of
approximately 0.4% per degree Celsius rise above standard test conditions of 25°C
[19], [20].
Material Degradation
Impact Assessment and Case Studies. Evaluating the real-world consequences of environmental stressors
requires a comprehensive analysis of empirical data gathered from diverse geographical installations to quantify
the magnitude of efficiency losses.
By examining performance data across distinct climatic zones, researchers can identify specific environmental
stressors that disproportionately affect energy yield, such as the severe efficiency penalties observed in arid
regions due to dust accumulation or the thermal losses prevalent in tropical areas with high ambient temperatures.
Fig 1.1. Effect of temperature on Efficiency
These findings underscore the necessity for region-specific performance modelling to accurately predict energy
yields and optimize system configurations for local environmental conditions.
Regional Variations in Performance Loss
Geographical location plays a decisive role in determining the magnitude and nature of efficiency losses, as
distinct climatic zones impose unique combinations of thermal stress, soiling rates, and meteorological
conditions on photovoltaic arrays.
For instance, installations in arid desert environments frequently experience substantial energy yield reductions
primarily due to high soiling rates and extreme ambient heat, whereas coastal deployments must contend with
corrosive salt mist accumulation and persistent humidity that accelerates material degradation.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 116
www.rsisinternational.org
Fig 1.2. Environmental Stressor model
Conversely, systems situated in high-altitude or temperate regions often benefit from increased irradiance levels
and lower ambient temperatures, which can enhance voltage output and overall system efficiency, provided that
other meteorological factors such as cloud cover and wind patterns remain favourable.
Fig 1.3. Energy Yeild Vs Region
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 117
www.rsisinternational.org
Economic Implications of Decreased Efficiency
The financial viability of solar energy projects is directly compromised by environmental factors that reduce
energy yield, as even minor efficiency declines can significantly extend the payback period and lower the
levelized cost of electricity. Furthermore, the unpredictability of environmental degradation introduces
additional risk premiums that can deter potential investors and complicate the financing models required for
large-scale solar infrastructure development.
Geographical location plays a decisive role in determining the magnitude and nature of efficiency losses, as
distinct climatic zones impose unique combinations of thermal stress, soiling rates, and meteorological
conditions on photovoltaic arrays
[2], [21]. For instance, installations in arid desert environments frequently
experience substantial energy yield reductions primarily due to high soiling rates and extreme ambient heat,
whereas coastal deployments must contend with corrosive salt mist accumulation and persistent humidity that
accelerates material degradation [2], [14]. Conversely, systems situated in high-altitude or temperate regions
often benefit from increased irradiance levels and lower ambient temperatures, which can enhance voltage output
and overall system efficiency, provided that other meteorological factors such as cloud cover and wind patterns
remain favorable
[2], [22].
Economic Implications of Decreased Efficiency
The financial viability of solar energy projects is directly compromised by environmental factors that reduce
energy yield, as even minor efficiency declines can significantly extend the payback period and lower the
levelized cost of electricity. Furthermore, the unpredictability of environmental degradation introduces
additional risk premiums that can deter potential investors and complicate the financing models required for
large-scale solar infrastructure development
[23]. Long-term changes in solar irradiance, driven by climate
change and air pollutants, present challenges for maintaining PV efficiency [2].
Extreme weather events and shifting climatic patterns further exacerbate these risks, potentially accelerating
material degradation rates and necessitating more robust system designs to ensure long-term reliability
[2], [24].
Empirical studies indicate that combined environmental stressors can result in performance losses reaching up
to 6070%
[23], with specific factors such as dust accumulation capable of reducing output by as much as 60%
in desert regions [2]. These substantial losses highlight the critical need for proactive maintenance and
environmental adaptation strategies to preserve the economic and operational integrity of photovoltaic
installations
[2], [23]. Optimizing PV systems for diverse climates and mitigating environmental impacts on
productivity is crucial for the continued success of solar photovoltaics [2], [23].
Mitigation Strategies and Optimization Techniques
To counteract the detrimental effects of environmental stressors on photovoltaic performance, a multifaceted
approach encompassing proactive maintenance, thermal management, and technological adaptation is essential
for maximizing energy yield and ensuring long-term system reliability
[2]. Effective cleaning regimes are
fundamental to mitigating soiling losses, particularly in arid regions where dust accumulation can severely
obstruct incident sunlight and significantly reduce power output
[24]. Studies indicate that particulate matter
accumulation can degrade efficiency by up to 64%, with specific dust types like coal dust causing the most
severe reductions
[25], [26]. Consequently, implementing routine cleaning schedules and automated cleaning
systems is critical for maintaining optimal transmittance and minimizing the financial impact of soiling-related
energy losses
[23]. Beyond particulate removal, thermal management strategies are crucial for counteracting the
efficiency losses associated with elevated cell temperatures, which can significantly degrade voltage output and
accelerate material aging
[27]. Active and passive cooling techniques, such as forced air ventilation, water
spraying, or the integration of phase change materials, are employed to dissipate excess heat and maintain cell
temperatures within optimal ranges for photovoltaic conversion
[2], [28]. These thermal regulation mechanisms
are particularly vital in high-temperature climates where efficiency penalties are most pronounced, ensuring that
the operating temperature remains as close as possible to standard test conditions to maintain the levelized cost
of electricity [28], [29].
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 118
www.rsisinternational.org
Panel Design Modifications
Innovations in photovoltaic architecture and material selection play a pivotal role in enhancing resilience against
environmental stressors, with advanced encapsulation materials and anti-reflective coatings specifically
engineered to minimize optical losses and protect against moisture ingress or UV-induced degradation.
Additionally, bifacial cell designs have emerged as a significant advancement, allowing for the capture of
reflected light from the rear surface to increase overall energy generation while simultaneously reducing
sensitivity to specific angle-of-incidence losses. Solar tracking systems further enhance energy capture by
dynamically adjusting the orientation of photovoltaic modules to follow the sun's trajectory throughout the day,
thereby maximizing the angle of incidence and increasing total irradiance exposure compared to fixed-tilt
installations. These tracking mechanisms are categorized into single-axis systems, which rotate around one axis
to follow the sun's east-to-west path, and dual-axis systems, which adjust both azimuth and elevation angles to
maintain optimal perpendicular to the sun's rays throughout the year. While these tracking systems significantly
increase energy yield, they introduce additional mechanical complexity and maintenance requirements that must
be weighed against the gains in efficiency.
Tracking Systems
Solar tracking systems function by dynamically orienting photovoltaic modules to follow the sun's daily
trajectory, thereby maximizing the angle of incidence and increasing total irradiance exposure compared to
fixed-tilt installations
[30]. These mechanisms are categorized into single-axis systems, which rotate around one
axis to follow the sun's east-to-west path, and dual-axis systems, which adjust both azimuth and elevation angles
to maintain optimal perpendicularity to the sun's rays throughout the year
[30]. Research indicates that the
implementation of tracking technologies can significantly enhance energy generation, with the magnitude of
improvement dependent on variables such as geographical location, climate conditions, and the specific type of
tracking mechanism employed [31]. For instance, a case study in Incheon, South Korea, demonstrated that a
tracking photovoltaic system installed on a commercial building generated 26.8% to 35.5% more electricity
annually than a fixed system, while also showing promising life-cycle cost savings with a payback period of
approximately 8 years [32].
Further empirical evidence from studies in Turkey and Jordan reveals that dual-axis tracking systems can
increase power generation by 29.3% to 45.0% on specific days compared to fixed modules
[33]. However, the
selection between single-axis and dual-axis configurations involves trade-offs between cost-effectiveness and
energy yield optimization, as dual-axis systems offer superior performance through precise alignment in both
horizontal and vertical planes but entail higher initial costs and increased maintenance complexity due to the
additional moving parts [34], [35]. Despite the higher capital outlay, single-axis tracking systems frequently
present a more favorable balance between cost and performance for utility-scale applications, offering yield
improvements of 15% to over 37.5% relative to fixed-mounted installations depending on the location and solar
resource [36]. Floating photovoltaic systems represent another innovative design approach, particularly
advantageous in regions where land availability is constrained, as these installations leverage the cooling
properties of water bodies to enhance module efficiency while conserving terrestrial space
[31].
While these floating systems mitigate land-use conflicts and benefit from evaporative cooling, they must be
engineered to withstand unique environmental challenges such as wave action, humidity-induced corrosion, and
biofouling, which can potentially offset the efficiency gains if not properly managed through specialized
materials and maintenance protocols
[35], [37]. Techno-economic assessments further highlight that while dual-
axis trackers provide the maximum boost in power generation, they often result in extended payback periods
compared to fixed-tilt systems, whereas monthly manual tilt adjustments offer a practical compromise by
reducing payback times by approximately 8 months while increasing electricity generation by 3.6% to 5%
[36].
Consequently, the selection of an optimal tracking strategy requires a comprehensive evaluation of site-specific
meteorological conditions, financial constraints, and long-term maintenance projections to ensure that the chosen
technology delivers the most favorable return on investment over the system's operational lifespan [35], [36].
However, the decision to implement tracking systems must also account for potential drawbacks, as the dynamic
movement of modules may introduce additional thermal stress on solar cells, particularly when the tracking
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 119
www.rsisinternational.org
mechanism alters the airflow over the module surface or when high irradiance coincides with elevated ambient
temperatures
[14]. Furthermore, the mechanical complexity inherent in tracking technologies introduces
susceptibility to wear and tear, especially in harsh environments where moving parts are prone to degradation
and access to skilled technicians for repairs may be limited
[38].
Therefore, ongoing research is increasingly focused on developing cost-effective and reliable tracking solutions
that optimize the balance between enhanced energy yield and the total cost of ownership, particularly through
the design of low-cost dual-axis systems that have demonstrated efficiency improvements of up to 44.89% in
experimental settings
[39]. Despite these promising experimental results, the widespread adoption of tracking
technologies remains contingent upon overcoming challenges related to mechanical reliability, energy
consumption for operation, and the economic feasibility of implementation in diverse geographical regions
[33],
[40]. To address these operational challenges, recent advancements have integrated artificial intelligence and
machine learning techniques into tracking system designs, which are critical for enhancing the accuracy and
reliability of solar tracking while facilitating predictive maintenance and real-time monitoring to improve overall
system performance and reduce operating costs [33]. These intelligent systems utilize sophisticated sensors and
predictive algorithms to dynamically adjust panel orientation with high precision, thereby mitigating the
efficiency losses associated with suboptimal sun alignment and ensuring that photovoltaic arrays operate at peak
CONCLUSION
The comprehensive analysis of environmental parameters underscores the profound influence that factors such
as temperature, irradiance, soiling, and humidity exert on the operational efficiency of solar photovoltaic
systems, necessitating a holistic approach to system design and site selection. Future research must prioritize the
development of advanced materials and predictive maintenance technologies that can mitigate these
environmental stressors, thereby ensuring the long-term reliability and economic viability of solar energy
infrastructure in an increasingly variable global climate.
Specifically, the integration of artificial intelligence and machine learning algorithms offers a promising pathway
to optimize performance forecasting and operational resilience, as these technologies enable the recognition of
complex environmental patterns and facilitate predictive maintenance strategies that reduce long-term costs
[42],
[43]. By leveraging intelligent algorithms for real-time monitoring and adaptive control, these advanced systems
can significantly enhance energy yield while simultaneously addressing scalability concerns and minimizing the
environmental footprint associated with operational inefficiencies
[23], [44]. Ultimately, the successful
deployment of next-generation photovoltaic infrastructure will depend on the synergistic application of smart
materials and data-driven analytics to create resilient energy systems capable of withstanding diverse
environmental stressors
[45], [46]. This synergy is essential for minimizing the levelized cost of electricity and
ensuring the sustainability of solar power as a dominant component of the global renewable energy mix [42],
[46]. As the demand for clean energy accelerates, addressing the environmental vulnerabilities of photovoltaic
technology through continuous innovation and adaptive management strategies remains paramount to securing
a sustainable energy future
[29], [47]. Policymakers and industry stakeholders must therefore support the
implementation of favorable regulatory frameworks and financial incentives, such as tax credits and feed-in
tariffs, to accelerate the adoption of these advancedtechnologies and foster a robust renewable energy ecosystem
[14].
Collaborative efforts among researchers, industry executives, and policymakers are considered crucial for
addressing the increasing difficulties presented by climate change and ensuring the long-term sustainability,
efficiency, and efficacy of solar energy systems in a swiftly changing climate [28]. This comprehensive strategy
is essential for ensuring the future of renewable energy amid global environmental challenges [28]. Such
collaborative frameworks are vital for translating technological advancements into practical solutions that
enhance the resilience and cost-effectiveness of solar infrastructure worldwide
[46], [48]. These limitations,
which include suboptimal energy conversion efficiency, fluctuating energy supply, and thermal degradation,
highlight the necessity for continued innovation in adaptive photovoltaics and smart materials to enhance system
robustness and long-term sustainability [46]. By addressing these persistent challenges through interdisciplinary
research and strategic investment, the solar energy sector can overcome current barriers to efficiency and
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 120
www.rsisinternational.org
reliability, thereby solidifying its role as a cornerstone of the global transition toward a sustainable energy future
[39], [46].
REFERENCES
1. L. T.A. and T. Igbawua, “Environmental Factors and the Performance of PV Panels: An Experimental
Investigation,” African Journal of Environment and Natural Science Research, vol. 6, no. 3, p. 231, Dec.
2023, doi: 10.52589/ajensr-ga3smdhp.
2. O. Bamisile, C. Acen, D. Cai, Q. Huang, and I. Staffell, The environmental factors affecting solar
photovoltaic output,” Renewable and Sustainable Energy Reviews, vol. 208, p. 115073, Nov. 2024, doi:
10.1016/j.rser.2024.115073.
3. P. Sarmah et al., Comprehensive Analysis of Solar Panel Performance and Correlations with
Meteorological Parameters,” ACS Omega, vol. 8, no. 50, p. 47897, Dec. 2023, doi:
10.1021/acsomega.3c06442.
4. J. Ballina and Y. I. Go, “Quantification and Comparative Analysis of Environmental Factors to Large-
Scale Solar Plant’s Energy Performance via Regression and Linear Correlation Models,” Journal of
Energy and Power Technology, vol. 7, no. 1, p. 1, Jan. 2025, doi: 10.21926/jept.2501001.
5. B. Zaidi, “Introductory Chapter: Introduction to Photovoltaic Effect,” in InTech eBooks, 2018. doi:
10.5772/intechopen.74389.
6. M. K. El-Adawi and I. A. Al-Nuaim, “The temperature functional dependence of VOC for a solar cell in
relation to its efficiency new approach,” Desalinati, vol. 209, p. 91, Apr. 2007, doi:
10.1016/j.desal.2007.04.014.
7. J. D. Stachiw, Performance of photovoltaic cells in an undersea environment / J.D. Stachiw. 1979. doi:
10.5962/bhl.title.47314.
8. L. Arivuselvam, D. Sakthi, P. Sakthivel, P. M. Anbarasan, and V. Aroulmoji, Irradiance Dependence on
Performance of Dye Sensitized andV-Grooved Silicon Solar Cells,” HAL (Le Centre pour la
Communication Scientifique Directe) Jan. 2015, Accessed: Oct. 2025. [Online]. Available:
https://hal.archives-ouvertes.fr/hal-03104526
9. C. Karaca and S. Yaver, Determining the Effect of Photovoltaic Module Surface Temperature on
Generation Efficiency, Ingeniería e Investigación, vol. 44, no. 2, May 2024, doi:
10.15446/ing.investig.106383.
10. G. S. Wahile et al., Performance analysis of photovoltaic panel using machine learning method,”
Indonesian Journal of Electrical Engineering and Computer Science , vol. 34, no. 1, p. 19, Feb. 2024, doi:
10.11591/ijeecs.v34.i1.pp19-30.
11. S. Diallo, F. Z. Melhaoui, M. Rafi, and A. Elassoudi, “Understanding Photovoltaic Module Degradation:
An Overview of Critical Factors, Models, and Reliability Enhancement Methods,” E3S Web of
Conferences, vol. 469, p. 11, Jan. 2023, doi: 10.1051/e3sconf/202346900011.
12. F. Shaik, L. S. Sundar, and P. Veeraboina, “Effect of various parameters on the performance of solar PV
power plant: a review and the experimental study,Sustainable Energy Research, vol. 10, no. 1. Apr. 10,
2023. doi: 10.1186/s40807-023-00076-x.
13. S. Adak, H. Cangi, and U. Arifoğlu, Improved software program for finding the series and parallel
resistances of the photovoltaic cell single diode equivalent circuit model based on the Newton-Raphson
method,Research Square (Research Square), Feb. 2024, doi: 10.21203/rs.3.rs-3969990/v1.
14. L. M. Shaker, A. A. Al‐Amiery, M. M. Hanoon, W. K. AlAzzawi, and A. A. H. Kadhum, “Examining
the influence of thermal effects on solar cells: a comprehensive review,” Sustainable Energy Research,
vol. 11, no. 1. Feb. 04, 2024. doi: 10.1186/s40807-024-00100-8.
15. S. R. P. Chitturi, E. Sharma, and W. Elmenreich, “Efficiency of photovoltaic systems in mountainous
areas,” p. 1, Jun. 2018, doi: 10.1109/energycon.2018.8398766.
16. C. H. Rossa, Energy losses in photovoltaic generators due to the wind patterns,” Research Square
(Research Square) , Mar. 2023, doi: 10.21203/rs.3.rs-2628850/v1.
17. R. M. Ehsan, S. P. Simon, K. Sundareswaran, K. A. Kumar, and T. Sriharsha, “Effects of nanocoatings on
the temperature-dependent cell parameters and power generation of photovoltaic panels,” Applied
Nanoscience, vol. 12, no. 12, p. 3945, Sep. 2022, doi: 10.1007/s13204-022-02633-0.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 121
www.rsisinternational.org
18. M. R. A et al., “Temperature-Induced Variations in Silicon Solar Cell Efficiency and Electrical
Characteristics,” International Journal of Research Publication and Reviews, vol. 6, no. 4, p. 6827, Apr.
2025, doi: 10.55248/gengpi.6.0425.14161.
19. K. Sheth and D. Patel, Comprehensive Examination of Solar Panel Design: A Focus on Thermal
Dynamics,” Smart Grid and Renewable Energy, vol. 15, no. 1, p. 15, Jan. 2024, doi:
10.4236/sgre.2024.151002.
20. K. Richard, K. J. Ukagwu, and W. Okafor, “Factors Influencing the Efficiency of Solar Energy Systems,
Journal of Engineering Technology and Applied Science (JETAS), vol. 6, no. 3, p. 119, Dec. 2024, doi:
10.36079/lamintang.jetas-0603.748.
21. S. Verma and D. K. Yadav, “Recent research and developments of degradation assessment and its
diagnosis methods for solar PV plant: a review,” International Journal of Applied Power Engineering
(IJAPE), vol. 13, no. 2. Institute of Advanced Engineering and Science (IAES), p. 483, Apr. 04, 2024. doi:
10.11591/ijape.v13.i2.pp483-498.
22. W. S. Ebhota and P. Y. Tabakov, Energy losses in crystalline silicon rooftop photovoltaic systems in
selected site locations in Sub-Saharan Africa,” International Journal of Renewable Energy Development,
vol. 13, no. 3, p. 508, Apr. 2024, doi: 10.61435/ijred.2024.57529.
23. E. H. Sepúlveda-Oviedo, “Impact of environmental factors on photovoltaic system performance
degradation,” Energy Strategy Reviews , vol. 59, p. 101682, Mar. 2025, doi: 10.1016/j.esr.2025.101682.
24. D. M. Atia, A. A. Hassan, H. T. El-Madany, A. Eliwa, and M. Zahran, “Degradation and energy
performance evaluation of mono-crystalline photovoltaic modules in Egypt,Scientific Reports, vol. 13,
no. 1, Aug. 2023, doi: 10.1038/s41598-023-40168-8.
25. D. Hameed et al., “Evaluation of self-cleaning mechanisms for improving performance of roof-mounted
solar PV panels: A comparative study, PLoS ONE, vol. 19, no. 10, Oct. 2024, doi:
10.1371/journal.pone.0309115.
26. S. Yakubu e al., “A holistic review of the effects of dust buildup on solar photovoltaic panel efficiency,”
Solar Compass, vol. 13, p. 100101, Dec. 2024, doi: 10.1016/j.solcom.2024.100101.
27. T. Rahman et al., “Investigation of Degradation of Solar Photovoltaics: A Review of Aging Factors,
Impacts, and Future Directions toward Sustainable Energy Management,” Energies, vol. 16, no. 9.
Multidisciplinary Digital Publishing Institute, p. 3706, Apr. 26, 2023. doi: 10.3390/en16093706.
28. P. C. Okonkwo et al., “Solar PV systems under weather extremes: Case studies, classification,
vulnerability assessment, and adaptation pathways,” Energy Reports, vol. 13, p. 929, Dec. 2024, doi:
10.1016/j.egyr.2024.12.067.
29. T. Rehman et al., “Global perspectives on advancing photovoltaic system performanceA state-of-the-
art review, Renewable and Sustainable Energy Reviews, vol. 207, p. 114889, Sep. 2024, doi:
10.1016/j.rser.2024.114889.
30. G. G. Ojo, O. A. Lottu, T. C. Ndiwe, U. Izuka, and N. N. -Ehiobu, “SOLAR ENERGY ADAPTATION
AND EFFICIENCY ACROSS DIVERSE NIGERIAN AND GLOBAL CLIMATES: A REVIEW OF
TECHNOLOGICAL ADVANCEMENT, Engineering Heritage Journal, vol. 7, no. 1. Zibeline
International Publishing, p. 99, Jan. 20, 2023. doi: 10.26480/gwk.01.2023.99.107.
31. K. Praveena et al., “A Review on Next-Generation Solar Solutions: Pioneering Materials and Designs for
Sustainable Energy Harvesting,” E3S Web of Conferences, vol. 505. EDP Sciences, p. 2004, Jan. 01, 2024.
doi: 10.1051/e3sconf/202450502004.
32. I. G. Wenten, K. Khoiruddin, and U. W. R. Siagian, Green Energy Technologies: A Key Driver in Carbon
Emission Reduction,” Journal of Engineering and Technological Sciences, vol. 56, no. 2, p. 143, Apr.
2024, doi: 10.5614/j.eng.technol.sci.2024.56.2.1.
33. H. A. Kazem, M. T. Chaichan, A. H. A. Al‐Waeli, and K. Sopian, Recent advancements in solar
photovoltaic tracking systems: An in-depth review of technologies, performance metrics, and future
trends,” Solar Energy, vol. 282, p. 112946, Sep. 2024, doi: 10.1016/j.solener.2024.112946.
34. M. Raza, “Automatic Solar Tracking System,” International Journal for Research in Applied Science and
Engineering Technology, vol. 13, no. 4, p. 5863, Apr. 2025, doi: 10.22214/ijraset.2025.69625.
35. N. G. Rajkumar, Govindhavasan, Jeyasri, A. Kumar, and A. Mahilarasi, “Solar Tracking Methods: A
Comprehensive Survey, International Journal for Research in Applied Science and Engineering
Technology, vol. 12, no. 4, p. 4361, Apr. 2024, doi: 10.22214/ijraset.2024.60975.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
Page 122
www.rsisinternational.org
36. A. E. Gol and M. Ščasný, Techno-economic analysis of fixed versus sun-tracking solar panels,”
International Journal of Renewable Energy Development, vol. 12, no. 3, p. 615, May 2023, doi:
10.14710/ijred.2023.50165.
37. A. Sabban et al., Advances in Green Electronics Technologies in 2023. IntechOpen, 2022. doi:
10.5772/intechopen.100759.
38. A. Gedifew and A. Benor,Evaluating the impact of tilt angles and tracking mechanisms on photovoltaic
modules in Ethiopia,” Frontiers in Energy Research, vol. 12, Jan. 2025, doi: 10.3389/fenrg.2024.1519725.
39. M. Dada and A. P. I. Popoola, Recent advances in solar photovoltaic materials and systems for energy
storage applications: a review,” Beni-Suef University Journal of Basic and Applied Sciences, vol. 12, no.
1. Springer Science+Business Media, Jul. 17, 2023. doi: 10.1186/s43088-023-00405-5.
40. N. J. Eyring and N. Kittner, “High-resolution electricity generation model demonstrates suitability of high-
altitude floating solar power,” Carolina Digital Repository (University of North Carolina at Chapel Hill),
May 2022, doi: 10.17615/x5p9-wm74.
41. K. Thopate, “IoT-driven Solar Tracking System for Reliable and Efficient Energy Generation,”
International Journal for Research in Applied Science and Engineering Technology, vol. 11, no. 5, p.
5193, May 2023, doi: 10.22214/ijraset.2023.52767.
42. R. V. Vichare and S. R. Gaikwad, “AI-based predictive maintenance of solar photovoltaics systems: a
comprehensive review,” Energy Informatics, vol. 8, no. 1, Oct. 2025, doi: 10.1186/s42162-025-00594-6.
43. A. Kumar, A. K. Dubey, I. S. Ramírez, A. M. del Río, and F. P. G. Márquez, “Artificial Intelligence
Techniques for the Photovoltaic System: A Systematic Review and Analysis for Evaluation and
Benchmarking,”Archives of Computational Methods in Engineering , vol. 31, no. 8. Springer
Science+Business Media, p. 4429, May 08, 2024. doi: 10.1007/s11831-024-10125-3.
44. L. D. Jathar et al., “A comprehensive analysis of the emerging modern trends in research on photovoltaic
systems and desalination in the era of artificial intelligence and machine learning,” Heliyon , vol. 10, no.
3, Feb. 2024, doi: 10.1016/j.heliyon.2024.e25407.
45. L. D. Jathar et al., Comprehensive review of environmental factors influencing the performance of
photovoltaic panels: Concern over emissions at various phases throughout the lifecycle,” Environmental
Pollution, vol. 326. Elsevier BV, p. 121474, Mar. 23, 2023. doi: 10.1016/j.envpol.2023.121474.
46. U. Mamodiya, I. Kishor, R. Garine, P. Ganguly, and N. Naik, “Artificial intelligence based hybrid solar
energy systems with smart materials and adaptive photovoltaics for sustainable power generation,”
Scientific Reports, vol. 15, no. 1, p. 17370, May 2025, doi: 10.1038/s41598-025-01788-4.
47. P. Kaledio and O. Favour, Optimizing Solar Panel Efficiency for Different Weather Conditions,” SSRN
Electronic Journal, Jan. 2024, doi: 10.2139/ssrn.4888827.
48. T. H. Nguyen, P. Paramasivam, V. H. Dong, H. C. Le, and D. C. Nguyen, “Harnessing a Better Future:
Exploring AI and ML Applications in Renewable Energy,” JOIV International Journal on Informatics
Visualization, vol. 8, no. 1, p. 55, Mar. 2024, doi: 10.62527/joiv.8.1.2637.