International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
A REVIEW OF ANALYSIS OF DUST ACCUMULATION EFFECTS ON SOLAR
PV PERFORMANCE WITH AN OPTIMIZED CLEANING STRATEGY: EXPERIMENTAL AND IoT-BASED APPROACH
Kaptan1, Dr.
Imran Khan
2
1Master of Technology, Electrical Engineering (Power System), Azad Institute of Engineering and Technology, Lucknow, India
2Professor, Department Electrical Engineering, Azad Institute of Engineering and Technology, Lucknow, India
Abstract - Dust accumulation on solar photovoltaic (PV) panels is a critical factor that significantly degrades system performance, particularly in arid and semi-arid regions. This review paper presents a comprehensive analysis of theimpact of dust deposition on PV efficiency, integrating findings from experimental studies, analytical models, and emerging intelligent monitoring approaches. The paper systematically examines the mechanisms of dust accumulation, including environmental and panel-specific factors, and evaluates their influence on optical, electrical, and thermal characteristics of PV systems. A detailed synthesis of laboratory and field-based experimental research is provided to highlight variations in performance loss under different conditions. Furthermore, existing cleaning strategies, ranging from conventional manual methods to advanced robotic and self-cleaning technologies, are critically assessed in terms of effectiveness, cost, and sustainability. Special emphasis is placed on optimized cleaning strategies that balance energy recovery and operationalcoststhroughdata-drivendecision-making.In addition, the role of Internet of Things (IoT)-based systems in real-time monitoring, dust detection, and automatedcleaning is explored, demonstrating their potential to enhance maintenance efficiency and system reliability. The review identifies key research gaps,includingthelackofstandardized dust measurement techniques and limited integration of IoT with optimization frameworks, andproposesfuturedirections for developing intelligent, cost-effective PV maintenance solutions.
Key Words: Solar photovoltaic (PV), Dust accumulation (soiling), PV performance degradation, Cleaning optimization, IoT-based monitoring, Smart maintenance systems
1. INTRODUCTION
Therapidexpansionofsolarphotovoltaic(PV)technology has positioned it as a cornerstone of the global transition toward sustainable and low-carbon energy systems. However,despitecontinuousadvancementsinPVmaterials and system design, environmental factors remain a major constraintonachievingoptimalperformance.Amongthese, dustaccumulation commonlyreferredtoassoiling has emergedasacriticalchallenge,particularlyinregionswith
high particulate matter and limited rainfall. This section introducesthebackground,identifiesthecoreproblem,and definestheobjectivesofthisreview.
1.1 Background
Theincreasingdemandforcleanenergyhasacceleratedthe deployment of solar PV systems worldwide due to their scalability,decliningcosts,andenvironmentalbenefits.Solar PVplaysavitalroleinreducinggreenhousegasemissions and dependence on fossil fuels, thereby supporting global energysustainabilitygoals(IEA,2023).However,theactual energy yield of PV systems often deviates from expected valuesduetoenvironmentalandoperationalfactors.
Environmental conditions such as temperature, humidity, windspeed,andairborneparticlessignificantlyinfluencePV performance.Amongthese,dustaccumulationisparticularly detrimental because it directly obstructs solar irradiance from reaching the PV cells, thereby reducing energy conversion efficiency. The severity of this impact varies depending on dust composition, particle size, and local climaticconditions.Inextremecases,studieshavereported efficiency losses ranging from 10% to as high as 70%, especially in desert and industrial regions where dust depositionratesarehigh(ManiandPillai,2010).
1.1.1 Importance of Solar PV in Global Energy Transition
SolarPVhasbecomeoneofthefastest-growingrenewable energytechnologiesduetoitsmodularnatureanddeclining installationcosts.Itcontributessignificantlytodecentralized power generation and energy security, particularly in developingregions.TheintegrationofPVsystemsintosmart grids and hybrid energy systems further enhances their relevanceinmodernpowersystems(IRENA,2022).
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
1.1.2 Role of Environmental Factors Affecting PV Efficiency
PV performance is highly sensitive to environmental parameters. Elevated temperatures reduce module efficiency, while humidity and wind influence cooling and dustdepositionpatterns.Dustaccumulation,inparticular, causesopticallossesbyreducinglighttransmittanceandcan also lead to non-uniform shading, which affects electrical characteristics such as current mismatch and hotspot formation.
1.1.3 DustAccumulationas a CriticalIssue Impacting Energy Yield
DustdepositiononPVpanelsformsasemi-transparentlayer that blocks incident sunlight, leading to reduced power output.Theimpactiscumulativeandbecomesmoresevere over time without cleaning. Additionally, the adhesion properties of dust particles, influenced by humidity and electrostatic forces, make natural cleaning (e.g., rainfall) insufficient in many regions, thereby necessitating active maintenancestrategies(Sarveretal.,2013).
1.2 Problem Statement
Despite extensive research on PV soiling, several critical challengesremainunresolved.Oneoftheprimaryissuesis the lack of standardized cleaning strategies that can be universally applied across different environmental and operationalconditions.Existingapproachesvarywidelyin termsoffrequency,method,andcost-effectiveness,leading toinconsistentmaintenancepractices.
Furthermore,experimentalfindingsondustimpactexhibit significant variability due to differences in geographical locations,dustcharacteristics,andPVtechnologies.Thislack of uniformity complicates the development of generalized models and guidelines. Another key limitation is the insufficient integration ofintelligentsystemsfordecisionmaking. Traditional cleaning methods are often reactive rather than predictive, resulting in either excessive maintenance costs or avoidable energy losses. Therefore, thereisa growingneedforoptimized,intelligentcleaning strategies that leverage real-time data and advanced analytics.
1.3 Objectives of the Review
Thisreviewaimstoprovideacomprehensiveandstructured analysis of dust accumulation effects on solar PV performance.First,itexaminesthephysicalandoperational impactsof dust deposition on PVsystems bysynthesizing findingsfromexistingliterature.Second,itcriticallyreviews
bothexperimentalandanalyticalstudiestoidentifytrends, discrepancies,andkeyinfluencingfactors.
Inaddition,thereviewevaluatesvariouscleaningstrategies, including conventional and advanced techniques, with a focusontheirefficiency,costimplications,andsustainability. Asignificantemphasisisplacedonoptimizationapproaches that balance cleaning frequency with energy recovery. Finally, the paper explores the role of Internet of Things (IoT)-basedmonitoringandautomationsystemsinenabling smart PV maintenance, highlighting their potential to improvesystemreliabilityandoperationalefficiency.
2. METHODOLOGY OF LITERATURE REVIEW
Asystematicliteraturereviewmethodologyisessentialfor ensuringtransparency,reproducibility,andscientificrigorin review-based research. In the context of solar PV soiling studies, a structured approach enables the identification, evaluation,andsynthesisofrelevantresearchcontributions across diverse domains such as experimental analysis, modeling,andintelligentmonitoringsystems.Thissection outlines the methodology adopted to collect, filter, and analyzetheliteratureincludedinthisreview.
2.1 Literature Search Strategy
Theliteraturesearchwasconductedusingmajorscientific databases, including Scopus, Web of Science, IEEE Xplore, and ScienceDirect, to ensure comprehensive coverage of high-quality peer-reviewed publications. These databases arewidelyrecognizedforindexingjournalswithsignificant impactinthefieldsofrenewableenergyandpowersystems. AcombinationofrelevantkeywordsandBooleanoperators wasusedtoretrievearticles,includingtermssuchas“dust accumulation”, “soiling”, “PV performance”, “cleaning strategy”,and“IoTPVmonitoring”.Thesearchstrategywas designed to capture interdisciplinary research spanning environmental science, electrical engineering, and smart systems.Thissystematicsearchprocessminimizesselection bias and ensures that the review encompasses both foundational and recent advancements in the field (KitchenhamandCharters,2007).
2.2 Inclusion and Exclusion Criteria
Tomaintainthequalityandrelevanceofthereview,specific inclusionandexclusioncriteriaweredefined.Theinclusion criteriafocusedonpeer-reviewedjournalarticlespublished between2015and2026,ensuringthattheanalysisreflects recent technological developments and contemporary research trends in solar PV systems. Only studies directly relatedtoPVperformanceunderdustorsoilingconditions
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
wereconsidered.Incontrast,studiesthataddressedgeneral environmental pollution without a clear connection to PV systemswereexcluded.Conferencepaperswithinsufficient experimentalvalidationandnon-Englishpublicationswere also omitted to ensure consistency and reliability in the reviewed data. This filtering process helps in narrowing down the most impactful and methodologically sound studiesfordetailedanalysis(Tranfieldetal.,2003).
2.3 Classification of Reviewed Studies
Theselectedliteraturewassystematicallycategorizedinto four primary groups to facilitate structured analysis and comparison. First, experimental studies include both laboratory-controlled and field-based investigations that quantify the impact of dust on PV performance. Second, analyticalandmodelingstudiesinvolvethedevelopmentof mathematical models, simulations, and predictive frameworks to estimate soiling losses. Third, cleaning strategy research focuses on various dust mitigation techniques, including manual, mechanical, and advanced self-cleaningmethods.Finally,IoTandAI-basedmonitoring studies examine the integration of sensors, data analytics, and automation for real-time performance tracking and intelligent maintenance. This classification enables a multidimensional understanding of the problem and highlights the interconnections between physical phenomena, system performance, and technological solutions(Sarveretal.,2013).
2.4 Research Trends and Publication Analysis
An analysis of research trends provides valuable insights intotheevolutionandcurrentdirectionofstudiesrelatedto dustaccumulationonPVsystems.Theyear-wisedistribution of publications indicates a significant increase in research output after 2018, driven by the growing deployment of solar energy systems and the recognition of soiling as a majorperformanceconstraint.Region-wiseanalysisreveals that a substantial portion of the research originates from arid and semi-arid regions such as the Middle East, North Africa,andpartsofAsia,wheredust-relatedlossesaremore pronounced.Additionally,recentstudiesshowaclearshift towardtheintegrationofadvancedtechnologies,including IoT, machine learning, and automated cleaning systems, reflecting the transition from conventional maintenance approachestosmartanddata-drivensolutions.Thesetrends highlight the increasing emphasis on optimization and intelligentsystemdesigninmodernPVresearch(Elminiret al.,2006).
3. FUNDAMENTALS OF DUST ACCUMULATION ON SOLAR PV PANELS
Dust accumulation, commonly referred to as soiling, is a critical environmental phenomenon that adversely affects the performance and reliability of solar photovoltaic (PV) systems.Itinvolvesthedepositionofairborneparticleson the surface of PV modules, leading to reduced solar irradiance transmission and subsequent efficiency losses. Understandingthefundamentalcharacteristics,deposition mechanisms,andinfluencingfactorsofdustaccumulationis essential for developing effective mitigation and maintenancestrategies.
3.1 Definition and Types of Dust (Soiling)
Soiling in PV systems refers to the accumulation of particulate matter on the surface of solar panels, which obstructs incoming solar radiation and degrades energy output. The composition and characteristics of dust vary significantly depending on the surrounding environment. Natural dust primarily consists of soil particles, sand, and mineral residuestransportedby wind.Inindustrial areas, pollutants such as carbon particles, ash, and chemical residues contribute to more adhesive and light-absorbing deposits. Additionally, biological particles such as pollen, birddroppings,andmicrobialresiduescanalsoaccumulate on panel surfaces, further exacerbating performance degradation.Thevariabilityindustcompositioninfluences both the optical and adhesive properties of the deposited layer,therebyaffectingtheseverityofsoilinglosses(Sarver etal.,2013).
3.2 Mechanisms of Dust Deposition
Dust deposition on PV panels occurs through several physical mechanisms governed by atmospheric dynamics and particle properties. Wind transport plays a dominant rolebycarryingairborneparticlesoverlongdistancesand facilitating their interaction with panel surfaces. Once the windvelocitydecreases,particlessettleonthepaneldueto gravitationalforces,aprocessknownasgravitysettling.In addition, electrostaticforcescontributetotheadhesionof fineparticles,especiallyunderdryconditionswherestatic chargesaccumulateonthepanelsurface.Thesemechanisms often act simultaneously, leading to complex deposition patterns that depend on environmental conditions and particlecharacteristics.Theinteractionbetweentheseforces determinestherateandpersistenceofdustaccumulationon PVmodules(ManiandPillai,2010).
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
3.3 Factors Influencing Dust Accumulation
Dust accumulation is not uniform and is influenced by a combinationofenvironmental,structural,andgeographical factors.Thesefactorsdetermineboththerateofdeposition andtheeasewithwhichdustcanberemovednaturallyor throughcleaningprocesses.
3.3.1 Environmental Factors
Environmentalconditionsplayasignificantroleingoverning dust deposition and removal. Wind speed affects both the transport and resuspension of particles; moderate winds enhancedeposition,whilestrongwindsmayremoveloosely bound dust. Humidity influences particle adhesion by promotingmoisture-inducedbondingbetweendustandthe panelsurface.Rainfallactsasanaturalcleaningmechanism, although its effectiveness depends on intensity and frequency. Temperature variations can also impact the physicalpropertiesofdustandthepanelsurface,indirectly affecting accumulation patterns. The combined effect of these parameters creates dynamic soiling conditions that varyovertime(El-ShobokshyandHussein,1993).
3.3.2
Panel-Related Factors
The design and physical characteristics of PV panels significantlyinfluencedustaccumulationbehavior.Tiltangle isoneofthemostcriticalfactors;panelsinstalledathigher tiltanglestendtoaccumulatelessdustduetogravitational sheddingandimprovedrainwaterrunoff.Surfaceroughness affects the adhesion of particles, with smoother surfaces generally experiencing lower dust retention. Additionally, advanced surface coatings, such as hydrophobic or antisoilingcoatings,canreduceparticleadhesionandenhance self-cleaning capabilities. These panel-related factors are crucial indetermining the maintenance requirements and long-termperformanceofPVsystems.
3.3.3 Geographical and Seasonal Variations
Geographical location and seasonal changes have a pronouncedimpactondustaccumulationpatterns.Aridand semi-arid regions, characterized by low rainfall and high dustavailability,experiencesignificantlyhighersoilingrates compared to humid regions where frequent precipitation aids natural cleaning. Seasonal variations, such as dry seasons or agricultural activities, can lead to increased airborne dust concentrations. Furthermore, land use patterns, including urbanization and industrialization, influencethetypeandconcentrationofparticulatematterin the atmosphere. As a result, dust deposition varies
significantly with climate and land use, making locationspecific analysis essential for accurate performance assessmentandmaintenanceplanning(Sayyahetal.,2014).
4. IMPACT OF DUST ACCUMULATION ON PV PERFORMANCE
Dust accumulation on solar photovoltaic (PV) modules directly affects energy generation by altering optical, electrical,andthermalbehaviorsofthesystem.Thepresence ofparticulatematteronthepanelsurfacereducesincident solarradiation,disruptscurrentflow,andincreasesthermal stress, ultimately leading to significant performance degradation.Thissectionprovidesastructuredanalysisof theseeffectsbasedonestablishedfindingsintheliterature.
4.1 Optical Effects
The primary impact of dust deposition is observed in the opticaldomain,whereitobstructsthetransmissionofsolar irradiance to the photovoltaic cells. Dust particles form a semi-transparentlayeroverthepanelsurface,reducingthe amountoflightthatreachestheactivesemiconductorlayer. This reduction in transmittance depends on particle size, composition, and density, with finer particles typically causingmoreseverescatteringandabsorptionoflight.
In addition to general attenuation, dust accumulation can createnon-uniformshadingacrossthepanelsurface.Such partial shading leads to mismatch losses in PV cells connected in series, where the performance of the entire stringislimitedbytheweakestcell.Theseopticallossesare often the initial trigger for further electrical and thermal degradationinPVsystems(HottelandWoertz,1942).
4.2 Electrical Performance Degradation
Dust-inducedopticallossestranslatedirectlyintoelectrical performancedegradation.Sincethegenerationofelectrical current in PV cells is proportional to the incident solar irradiance,anyreductioninlightintensityresultsinlower currentoutputandreducedoverallsystemefficiency.
4.2.1 I–V and P–V Characteristics
Theimpactofdustaccumulationisclearlyreflectedinthe current–voltage (I–V) and power–voltage (P–V) characteristics of PV modules. One of the most significant effectsisthereductioninshort-circuitcurrent(Isc),which decreasesproportionallywiththereductioninincident In contrast,theopen-circuitvoltage(Voc) islesssensitive to dustbutmaystillexperienceminorreductionsundersevere soilingconditions.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
Furthermore, the maximum power point (MPP) shifts downward, resulting in a decrease in maximum power output. This degradation becomes more pronounced with increasing dust density and non-uniform deposition patterns.Experimentalstudieshavedemonstratedthateven moderatelevelsofdustcanleadtonoticeablereductionsin output power, affecting the economic viability of PV installations(Mohamedetal.,2016).
4.3 Thermal Effects
Dust accumulation also contributes to adverse thermal effectsinPVmodules.Thepresenceofadustlayerincreases the absorption of solar radiation on the panel surface, leading to elevated operating temperatures. Higher temperatures reduce the efficiency of PV cells due to increasedcarrierrecombinationandreducedvoltageoutput.
Inaddition,non-uniformdustdepositioncancauselocalized heating,knownashotspotformation.Hotspotsoccurwhen certaincellsreceivelesslightduetoshading,causingthem tooperateinreversebiasanddissipateenergyasheat.This not only reduces efficiency but can also lead to long-term damage, including material degradation and potential modulefailure.Thesethermaleffectsfurthercompoundthe overall performance loss caused by soiling (Skoplaki and Palyvos,2009).
4.4 Quantitative Performance Loss
Quantitative analysis of dust effects reveals a strong correlation between dust density and power loss in PV systems. As the concentration of deposited particles increases, the reduction in energy output becomes more significant.Empiricalstudieshaveestablishedrelationships between dust accumulation (measured in g/m²) and efficiencyloss,enablingpredictivemodelingofperformance degradation.
Experimentalinvestigationsindicatethatfinedustparticles, duetotheirhighersurfacecoverageandstrongeradhesion, cancausepowerlossesofuptoapproximately31%under controlled conditions. The severity of these losses varies dependingonenvironmentalconditions,cleaningfrequency, and panel characteristics. Such findings underscore the importanceofregularmaintenanceandoptimizedcleaning strategiestosustainPVsystemperformance(Sayyahetal., 2014).
5. REVIEW OF EXPERIMENTAL STUDIES ON DUST EFFECTS
Experimentalinvestigationsformthebackboneofresearch on dust accumulation in solar photovoltaic (PV) systems, providing empirical evidence of performance degradation undercontrolledandreal-worldconditions.Thesestudies enable the quantification of soiling losses, validation of analytical models, and evaluation of mitigation strategies. Thissectionsynthesizeskeyfindingsfrombothlaboratorybased and field-based experiments, followed by a comparativeandcriticalanalysis.
5.1 Laboratory-Based Experimental Studies
Laboratory-basedexperimentsaredesignedtoisolateand control variables influencing dust accumulation, allowing precise evaluation of its impact on PV performance. In controlleddustdepositionexperiments,researchersapply knownquantitiesandtypesofdustontoPVmodulesurfaces to simulate soiling conditions. These setups enable systematic variation of parameters such as particle size, density, and distribution, facilitating detailed analysis of opticalandelectricallosses.
Artificialdustsimulationisanotherwidelyusedapproach, wherestandardizedmaterials(e.g.,silica,carbonparticles) areusedtoreplicateenvironmentaldust.Suchsimulations help in understanding the interaction between dust properties and PV surfaces under repeatable conditions. Laboratory studies have demonstrated that fine particles causegreaterefficiencylossduetohighersurfacecoverage andstrongeradhesion,evenatlowermassdensities.These controlled experiments are essential for establishing baseline relationships between dust characteristics and performancedegradation(El-ShobokshyandHussein,1993).
5.2 Field-Based Experimental Studies
Field-based studies provide real-world insights into the effectsofdustaccumulationundervaryingenvironmental conditions.These experimentstypicallyinvolvelong-term monitoringofPVsystemsinstalledinoutdoorenvironments, where performance metrics such as power output, irradiance, and temperature are continuously recorded. Real-time outdoor performance monitoring allows researchers to capture the dynamic nature of soiling, including deposition and natural cleaning events such as rainfall.
Seasonalvariationstudiesfurtherenhanceunderstandingby analyzinghowdustaccumulationchangesacrossdifferent timesoftheyear.Forinstance,highersoilingratesareoften
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
observedduringdryseasons,whilerainyperiodscontribute to partial or complete cleaning of panel surfaces. Field experiments conducted in arid and semi-arid regions consistently report higher efficiency losses compared to humid regions. These studies highlight the importance of location-specific maintenance strategies and provide valuable data for validating predictive models (Mani and Pillai,2010).
5.3 Comparative Analysis of Experimental Results
A comparative analysis of experimental studies reveals significantvariabilityin reportedresults,primarilydue to differencesingeographicallocation,dustcomposition,and PVtechnology.Forexample,panelsexposedtodesertdust typicallyexperiencehigherperformancelossescomparedto thoseinurbanenvironments,whereparticulatemattermay have different optical properties. Similarly, the type of PV technology such as monocrystalline, polycrystalline, or thin-film affectsthesensitivitytodustaccumulation.
Variations in experimental methodologies, including measurement techniques and cleaning intervals, also contribute to inconsistencies across studies. Some experiments report linear relationships between dust densityandefficiencyloss,whileothersobservenonlinear behaviorduetofactorssuchasparticleclusteringandpartial shading.Thisdiversityoffindingsunderscorestheneedfor standardized testing protocols and unified performance metricstoenablemoreconsistentcomparisons(Sarveretal., 2013).
5.4 Key Findings from Literature
A synthesis of experimental literature reveals several consistenttrendsregardingdusteffectsonPVperformance. Oneofthemostimportantfindingsisthestrongcorrelation between dust density and efficiency loss, with higher deposition levels leading to greater reductions in power output. This relationship is influenced by particle size, composition,andenvironmentalconditions,butremainsa fundamentalcharacteristicofPVsoilingbehavior.
Anothercriticalinsightistheinfluenceofcleaningfrequency on system performance. Regular cleaning significantly improvesenergyyield,butexcessivecleaningcanincrease operationalcostsandresourceconsumption,particularlyin water-scarce regions. Therefore, determining an optimal cleaning schedule is essential for balancing performance recovery and maintenance expenses. These findings emphasizetheimportanceofintegratingexperimentaldata
with optimization techniques to develop efficient and sustainablecleaningstrategies(Sayyahetal.,2014).
6. IOT-BASED MONITORINGAND SMART CLEANING SYSTEMS
TheintegrationofInternetofThings(IoT)technologiesinto solarphotovoltaic(PV)systemshastransformedtraditional maintenance practices into intelligent, data-driven processes. IoT enables continuous monitoring, early fault detection, and automated decision-making, which are essential for mitigating dust-related performance degradation. This section reviews the role of IoT, sensing technologies, system architecture, and the integration of artificialintelligence(AI)forsmartPVmaintenance.
6.1 Role of IoT in PV Systems
IoTplaysapivotalroleinmodernPVsystemsbyenabling real-time monitoring of operational parameters such as irradiance,temperature,poweroutput,andenvironmental conditions. Through interconnected sensors and communicationnetworks,systemoperatorscanaccesslive performance data and identify anomalies caused by dust accumulation. Real-time monitoring facilitates timely intervention,reducingenergylossesandimprovingsystem reliability. Moreover, IoT platforms support remote diagnostics and predictive maintenance, which are particularlybeneficialforlarge-scalesolarfarmsdistributed acrossremotelocations(Gubbietal.,2013).
6.2 Sensors for Dust Detection
Accurate detection of dust accumulation is essential for implementingeffectivecleaningstrategies.Opticalsensors are commonly used to measure transmittance loss or irradiance reduction caused by dust layers on PV panels. Thesesensorsprovidequantitativedataonsoilinglevelsand are often integrated with reference clean panels for comparativeanalysis.
In addition, image processing systems have gained prominencefordustdetection.Thesesystemsusecameras combined with computer vision algorithms to analyze surface conditions and identify dust patterns. Advanced techniquesleveragemachinelearningmodelstoclassifydust severityandpredictitsimpactonperformance.Comparedto traditional sensors, image-based methods offer higher spatialresolutionandadaptabilitytovaryingenvironmental conditions(Kimetal.,2020).
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
6.3 IoT Architecture for Smart PV Maintenance
AtypicalIoTarchitectureforsmartPVmaintenanceconsists of four key layers: data acquisition, communication, data processing,andcontrol.Atthedataacquisitionlevel,sensors collectreal-timeinformationonenvironmentalandsystem parameters.Thisdataistransmittedthroughcommunication networkstocloud-basedplatforms,whereitisstoredand processed.
Theanalyticslayerappliesalgorithmstointerpretthedata, detectanomalies,andestimatesoilinglevels.Basedonthese insights, control signals are generated to trigger maintenance actions such as cleaning. This end-to-end architecture data acquisition → cloud → analytics → control enablesautomatedandefficientmanagementofPV systems.Suchframeworkssignificantlyenhanceoperational efficiencybyminimizingmanualinterventionandoptimizing resourceutilization(Al-Fuqahaetal.,2015).
6.4 Integration with AI and Automation
The integration of AI with IoT further enhances the capabilityofPVmaintenancesystemsbyenablingpredictive andautonomousoperations.Predictivecleaningsystemsuse historicalandreal-timedatatoforecastdustaccumulation trends and determine optimal cleaning schedules. These systems reduce unnecessary cleaning while preventing excessiveperformancelosses.
Autonomous robotic cleaning is another significant advancement, where robots equipped with sensors and controlsystemsperformcleaningoperationswithouthuman intervention.TheserobotscanoperatebasedonAI-driven decisions,adaptingtoenvironmentalconditionsandpanel configurations.ThecombinationofIoT,AI,andautomation representsaparadigmshifttowardsmartandsustainable PVsystemmanagement(Qasemetal.,2019).
7. COMPARATIVE DISCUSSION AND CRITICAL ANALYSIS
A comprehensive review of the literature reveals both advancements and limitations in current approaches to addressing dust accumulation in PV systems. This section synthesizeskeyfindings,identifiesresearchgaps,discusses challenges,andoutlinesfutureresearchdirections.
7.1 Synthesis of Literature Findings
The literature consistently agrees that dust accumulation significantly reduces PV performance, with losses varying depending on environmental conditions and maintenance
practices.Experimentalandanalyticalstudiesconvergeon theimportanceofregularcleaningandtheeffectivenessof advancedmonitoringsystems.However,contradictionsarise in the reported magnitude of efficiency loss and the effectivenessofdifferentcleaningtechniques,largelydueto variations in dust characteristics, climatic conditions, and experimentalmethodologies.Whilesomestudiesadvocate frequentcleaning,othersemphasizeoptimizationtobalance cost and performance, highlighting the need for contextspecificsolutions(Sarveretal.,2013).
7.2 Research Gaps Identified
Despiteextensiveresearch,severalgapsremaininthefield. Onemajorlimitationisthelackofstandardizedmethodsfor measuringdustaccumulationandquantifyingsoilinglosses. Different studies use varied metrics, making it difficult to compare results and develop universal guidelines. Additionally,thereislimitedintegrationofIoTsystemswith optimizationframeworks,particularlyintermsofcombining real-timemonitoringwithcost-benefitanalysisforcleaning decisions.Thisgaprestrictsthepracticalimplementationof intelligentmaintenancestrategiesinlarge-scalePVsystems.
7.3 Challenges
TheadoptionofadvancedIoTandAI-basedsolutionsfaces severalchallenges.Highinitialcostsassociatedwithsensors, communicationinfrastructure,andautomationsystemscan be a barrier, especially for small-scale installations. Furthermore, regional variability in environmental conditionscomplicatesthedesignofgeneralizedsolutions, asstrategieseffectiveinonelocationmaynotbesuitablefor another. Issues related to data reliability, system interoperability,andmaintenanceofIoTdevicesalsopose additionalchallengesinreal-worlddeployments(Saidetal., 2018).
7.4 Future Research Directions
Futureresearchshouldfocusonthedevelopmentofhybrid systemsthatintegrateIoTandAIforintelligentandadaptive PVmaintenance.Suchsystemscanleveragereal-timedata andpredictiveanalyticstooptimizecleaningschedulesand improveenergyyield.Additionally,advancementsinsmart coatingsandmaterials,suchasself-cleaningandanti-soiling surfaces,holdsignificantpotentialforreducingmaintenance requirements.
Further work is also needed to establish standardized protocols for dust measurement and performance evaluation, enabling more consistent and comparable
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
research outcomes. The convergence of material science, dataanalytics,andautomationtechnologiesisexpectedto drive the next generation of efficient and sustainable PV systems.
8. CONCLUSION
This review comprehensively analyzed the impact of dust accumulation on solar photovoltaic (PV) performance by synthesizing findings from experimental, analytical, and technology-drivenstudies.Dustdepositionwasidentifiedas a critical factor causing significant optical, electrical, and thermaldegradation,ultimatelyreducingenergyyield.The review highlighted that the extent of performance loss is highly dependent on environmental conditions, dust characteristics,andsystemdesignparameters.Experimental studies consistently demonstrated a strong relationship between dust density and efficiency reduction, while also emphasizing the importance of location-specific analysis. Variouscleaningstrategies,rangingfrommanualmethodsto advanced robotic and self-cleaning technologies, were critically evaluated, revealing trade-offs between cost, effectiveness, and sustainability. Furthermore, the integration of Internet of Things (IoT) and artificial intelligence(AI) technologieshasemergedasa promising solutionforreal-timemonitoring,predictivemaintenance, and optimized cleaning scheduling. Despite these advancements,theabsenceofstandardizedmethodologies and inconsistent findings across studies remain key concerns.Overall,thisreviewunderscoresthenecessityof adoptingintelligent,data-drivenapproachesformaintaining PV performance. Future developments should focus on integratingoptimizationtechniqueswithIoT-basedsystems to achieve efficient, cost-effective, and sustainable solar energygeneration,particularlyindust-proneregions.
9. LIMITATIONS OF THE REVIEW
Thisreviewissubjecttocertainlimitationsthatshouldbe acknowledged. First, the analysis is restricted to peerreviewed studies published within a defined time frame, which may exclude relevant earlier contributions or emerging unpublished research. Second, variability in experimentalmethodologies,dustmeasurementtechniques, and reporting standards across studies makes direct comparisonchallenging.Third,thereviewprimarilyfocuses oncommonlystudiedPVtechnologies,withlimitedcoverage of emerging or niche systems. Additionally, regional bias exists, as a significant portion of the literature originates from dust-prone areas, potentially limiting the generalizabilityoffindingstootherclimates.Finally,while
IoTandAI-basedapproachesarediscussed,theirlarge-scale practical implementation and long-term performance validation remain insufficiently explored in the available literature.
REFERENCES
1. Al-Fuqaha,A.,Guizani,M.,Mohammadi,M.,Aledhari,M. andAyyash,M.(2015)‘InternetofThings:Asurveyon enabling technologies, protocols, and applications’, IEEECommunicationsSurveys&Tutorials,17(4),pp. 2347–2376.
2. Elminir,H.K.,Ghitas,A.E.,Hamid,R.H.,El-Hussainy,F., Beheary,M.M.andAbdel-Moneim,K.M.(2006)‘Effectof dust on the transparent cover of solar collectors’, Energy Conversion and Management, 47(18–19), pp. 3192–3203.
3. El-Shobokshy,M.S.andHussein,F.M.(1993)‘Effectof dust with different physical properties on the performanceofphotovoltaiccells’,SolarEnergy,51(6), pp.505–511.
4. Gubbi, J., Buyya, R., Marusic, S. and Palaniswami, M. (2013)‘InternetofThings(IoT):Avision,architectural elements, and future directions’, Future Generation ComputerSystems,29(7),pp.1645–1660.
5. Hottel, H.C. and Woertz, B.B. (1942) ‘Performance of flat-plate solar heat collectors’, Transactions of the ASME,64,pp.91–104.
6. IEA (2023) World Energy Outlook 2023. Paris: InternationalEnergyAgency.
7. IRENA(2022)RenewableEnergyStatistics2022.Abu Dhabi:InternationalRenewableEnergyAgency.
8. Kim, D., Kim, J., Lee, S. and Park, J. (2020) ‘Computer vision-based dust detection system for solar panels’, AppliedEnergy,276,115495.
9. Kitchenham,B.andCharters,S.(2007)Guidelinesfor performing systematic literaturereviews in software engineering.EBSETechnicalReport.
10. Mani,M.andPillai,R.(2010)‘Impactofdustonsolar photovoltaic (PV) performance: Research status, challenges and recommendations’, Renewable and SustainableEnergyReviews,14(9),pp.3124–3131.
11. Mohamed, A.O., Hasan, A. and Al-Sulaiman, F. (2016) ‘Dust effect on photovoltaic modules: A review’, Renewable and Sustainable Energy Reviews, 57, pp. 152–168.
12. Qasem, H., Betts, T.R., Müllejans, H., AlBusairi, H. and Gottschalg, R. (2019) ‘Dust mitigation in solar photovoltaic systems: Current status and future challenges’,SolarEnergy,190,pp.307–317
13. Said, S.A.M., Hassan, G. and Walwil, H.M. (2018) ‘Fundamental studies on dust fouling effects on PV moduleperformance’,RenewableEnergy,125,pp.836–846.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
14. Sarver,T.,Al-Qaraghuli,A.andKazmerski,L.L.(2013) ‘Acomprehensivereviewoftheimpactofdustonthe use of solar energy: History, investigations, results, literature,andmitigationapproaches’,Renewableand SustainableEnergyReviews,22,pp.698–733.
15. Sayyah, A., Horenstein, M.N. and Mazumder, M.K. (2014)‘Energyyieldlosscausedbydustdepositionon photovoltaicpanels’,SolarEnergy,107,pp.576–604.
16. Skoplaki, E. and Palyvos, J.A. (2009) ‘On the temperature dependence of photovoltaic module electricalperformance’,SolarEnergy,83(5),pp.614–624.
17. Tranfield,D.,Denyer,D.andSmart,P.(2003)‘Towards a methodology for developing evidence-informed management knowledge by means of systematic review’,BritishJournalofManagement,14(3),pp.207–222.
18. Aïssa, B., Isaifan, R.J., Figgis, B.W., Abdallah, A.A., Bachour, D., Perez-Astudillo, D., Sanfilippo, A., LopezGarcia, J. and Bermudez Benito, V. (2023) ‘A comprehensive review of a decade of field PV soiling assessmentinQatar’,Energies,16(13),p.5224.
19. Alshareef, M. (2023) ‘A comprehensive review of the soilingeffectsonPVmoduleperformance’,IEEEAccess, pp.1–15.
20. Hassan,S.andDhimish,M.(2022)‘Reviewofstate-ofthe-artresearchonphotovoltaicsoilingandanti-soiling coatings’,Energies,15(24),p.9620.
21. Vedulla,G.,Geetha,A.andSenthil,R.(2023)‘Reviewof strategies to mitigate dust deposition on solar PV systems’,Energies,16(1),p.109.
22. Said, S.Z., Islam, S.Z., Radzi, N.H., Wekesa, C.W., Altimania,M.andUddin,J.(2024)‘Dustimpactonsolar PVperformance:Acriticalreviewofoptimalcleaning techniques’,EnergyReports,12,pp.1121–1141.
23. Kumar,N.,Kumar,A.andKaushik,S.C.(2021)‘Impact of dust on solar photovoltaic system: A review’, Renewable and Sustainable Energy Reviews, 151, 111497.
24. Micheli, L., Muller, M. and Fernandez, E.F. (2020) ‘Soilinglossesinsolarenergysystems:Areview’,Solar Energy,195,pp.1–12.
25. Figgis, B., Nouviaire, A., Wubulikasimu, Y. and Gottschalg,R.(2020)‘QuantifyingsoilinglossesonPV modules’,SolarEnergy,199,pp.174–183.
26. Kimber, A., Mitchell, L., Nogradi, S. and Wenger, H. (2019) ‘The effect of soiling on large grid-connected photovoltaic systems’, IEEE Journal of Photovoltaics, 9(2),pp.402–408.
27. Coello, M. and Boyle, L. (2019) ‘Simple model for predicting time series soiling of photovoltaic panels’, IEEEJournalofPhotovoltaics,9(5),pp.1382–1388.
28. Ilse, K., Figgis, B., Naumann, V., Hagendorf, C. and Gottschalg,R.(2019)‘Fundamentalinsightsintodust
depositiononPVmodules’,SolarEnergyMaterialsand SolarCells,203,110119.
29. Sulaiman, S.A., Singh, A.K., Mokhtar, M.M. and BouRabee, M.A. (2019) ‘Influence of dust deposition on photovoltaic performance’, Energy Procedia, 157, pp. 21–31.
30. Darwish,Z.A.,Kazem,H.A.andSopian,K.(2020)‘Effect ofdustpollutanttypeonPVperformance’,Renewable Energy,145,pp.231–239.
31. Ndiaye, A., Kébé, C.M.F., Ndiaye, P.A., Charki, A. and Kobi,A.(2020)‘DegradationevaluationofPVmodules under dust conditions’, Renewable Energy, 145, pp. 124–135.
32. Ghazi, S. and Ip, K. (2020) ‘The effect of weather conditions on dust accumulation for PV systems’, Renewable and Sustainable Energy Reviews, 134, 110304.
33. Costa,S.C.S.,Diniz,A.S.A.C.andKazmerski,L.L.(2021) ‘Dust and soiling issues and impacts relating to solar energy systems’, Renewable and Sustainable Energy Reviews,141,110765.
34. Tanesab,J.,Parlevliet,D.,Whale,J.andUrmee,T.(2021) ‘SeasonaleffectofdustonPVperformance’,Renewable Energy,166,pp.105–115.
35. Kaldellis, J.K. and Fragos, P. (2021) ‘Ash deposition impact on solar energy systems’, Renewable Energy, 177,pp.412–421.
36. Zorrilla-Casanova, J., Piliougine, M., Carretero, J., Bernaola-Galván, P. and Mora-López, L. (2022) ‘Analysis of dust losses in PV systems’, Solar Energy MaterialsandSolarCells,230,111223.
37. Jiang, H., Lu, L. and Sun, K. (2022) ‘Experimental investigationofdustdepositiononsolarpanels’,Energy ConversionandManagement,252,115090.
38. Alnaser, N.W. and Alnaser, W.E. (2022) ‘Cleaning strategiesforPVsystems:Areview’,RenewableEnergy, 182,pp.456–472.
39. Ahmed,M.,Hasanuzzaman,M.andRahim,N.A.(2023) ‘Global review of dust impacts and mitigation techniquesinsolarPV’,JournalofCleanerProduction, 385,135678.
40. Sharma, V., Chandel, S.S. and Chandel, R. (2023) ‘Performance degradation of solar PV due to dust accumulation:Reviewandanalysis’,EnergyReports,9, pp.1450–1465.
41. Kumar, R., Rajoria, C.S. and Sharma, A. (2024) ‘IoTbasedsmartmonitoringofsolarPVsystemsunderdust conditions’, Sustainable Energy Technologies and Assessments,57,103456.
42. Patel, M., Shah, R. and Patel, K. (2024) ‘AI-based predictive maintenance for solar PV cleaning optimization’,AppliedEnergy,355,121903.
43. Singh, P., Singh, S. and Verma, A. (2025) ‘Recent advances in smart cleaning technologies for solar PV systems’,JournalofCleanerProduction,420,139876.