Effect of partial shading on photovoltaic systems performance and its mitigation techniques-a review

ABSTRACTThe installed capacity of photovoltaic (PV) systems is increasing at an exponential rate around the world because it has the potential to meet the ever-increasing demand for energy and simultaneously mitigate the climate change crisis. Sustained investment in this energy sector over the last two decades has enabled researchers to introduce innovations in all related aspects, including maximizing cell efficiency, optimizing manufacturing processes, building public opinion, and project financing. These advancements have made PV technology the most affordable energy technology globally.However, PV technology faces some inherent technical challenges that diminish its effectiveness in providing green energy leading to a lower scale of decarbonization. One of these challenges is the premature failure of PV modules due to a phenomenon called a hot spot under partial shading. Research shows that PV cells may potentially undergo reverse breakdown under partial shading conditions, leading to temperatures of up to 400°C. Such high temperatures not only reduce PV performance but also cause irreversible damage and premature module failure, and even fire in extreme cases. The extent of power output reduction depends on the shading pattern on a PV system, irradiation, geographical location, and time of the day. For example, a single shaded cell in a module can cause a power loss of up to 50%, while multiple shaded cells can lead to a reduction of up to 90%. On average, partial shading can cause a power loss of 10–15% in a PV system. In this paper, a comprehensive review on the theoretical background of reverse breakdown mechanisms in PV cells/systems and various techniques to mitigate the effects of partial shading has been carried out with an exhaustive literature survey. As of the current date, researchers have suggested using module-level power electronics (MLPEs) to increase the energy yield of shaded PV systems by 5–25%, depending on the shading conditions and the type of MLPE technology. Nevertheless, the use of maximum power point tracking (MPPT) can enhance the efficiency of shaded PV systems is proposed to have augmented up to 30%.KEYWORDS: Hot spotpartial shadingphotovoltaicsreverse breakdownMPPT Nomenclature Abbreviations=PV=PhotovoltaicPV-TE=PV-thermometricMC-FDTD=Monte Carlo-Finite Difference Time DomainCNT=Carbon NanotubeMLPEs=Module-Level Power ElectronicsPERC=Passivated Emitter and Rear CellAl-BSF=Aluminum Back Surface FieldPID=Potential Induced Degradationn-PERT=N-Type Passivated Emitter Rear Totally diffusedLSC PV=luminescent solar concentrator PVc-Si=Crystalline siliconPSC=partial shading conditionsMPP=Maximum Power PointMPPT=MPP TrackingDMPPT=Distributed MPPTBPD=Bypass DiodeSTC=standard test conditionsSubMICs=Submodule Integrated ConvertersMOSFET=Metal-Oxide-Semiconductor Field-Effect TransistorCSD=Conduction State DetectionIGBT=Insulated-Gate Bipolar TransistorNMOS=N-channel Metal-oxide SemiconductorPCM=phase-changing materialTCT=Total-Cross-TiedBL=Bridge-LinkHC=Honey CombSP=Series-ParallelPLC=Programmable Logic ControllerSCU=Supervision Control UnitSDKP=SuDoKu puzzledIC=Incremental ConductanceO-TCT=Optimal TCTRSP=Reconfigurable SPLS-TCT=Latin-based puzzle-based TCTM-TCT=Modified TCTNS=Novel StructureCDV=Cross Diagonal ViewKKSP=Ken-Ken Square puzzledWDO=Wind-Driven OptimizationDE=Differential EvolutionCS=Cuckoo SearchSCA=Sine-Cosine AlgorithmGA=Genetic AlgorithmHSA=Harmony Search AlgorithmPSO=Particle Swarm OptimizationEL-PSO=Enhanced Leader-PSOANN=Artificial Neural NetworkPWM=Pulse Width ModulationFSCC=Fractional Short Circuit CurrentEM=Electromagnetism-Like Mechanism AlgorithmHIT=Heterojunction with Intrinsic Thin layerGWO=Grey Wolf OptimizerBFO=Bacterial Foraging OptimizationIGD=Improved Gradient DescentGOA=Grasshopper Optimization AlgorithmP&O=Perturb & ObserveSymbol=VR=Reverse VoltageVF=Forward (Open Circuit) VoltageVD=Forward Voltage DropI-V=Current VoltageDisclosure statementWe hereby declare that there is no conflict of interest with regards to this article.Additional informationNotes on contributorsNikhil KushwahaNikhil Kushwaha received the B.Tech Degree in Electrical & Electronics Engineering from UPTU, Uttar Pradesh, India in 2010, The M.Tech Degree In Power System Engineering from National Institute of Technology, Hamirpur, India, in 2012. He is currently working toward the Ph.D. degree with Delhi Technological University, Delhi, India. His research interests include Solar Array PV Reconfiguration, Hot-spot mitigation, diagnostic and monitoring techniques for photovoltaic devices and systems.Vinod Kumar YadavVinod Kumar Yadav (Senior Member, IEEE) received the B. Tech. degree in electrical engineering from the Institute of Engineering and Technology, Bareilly, Idia, in 2003, the M. Tech. degree in power system engineering from the National Institute of Technology, Jamshedpur, India, in 2005, and the Ph.D. degree in power system engineering from the Indian Institute of Technology, Roorkee, India, in 2011. His research interests include renewable energy systems, power system planning and optimization, distributed generations, and smart grid.Radheshyam SahaRadheshyam Saha worked as the Chief Engineer at the Central Electricity Authority and is currently serving as a Professor in the Electrical Engineering Department at Delhi Technical University (DTU) in Delhi, India. He received his Ph.D. degree in FACTS Technology from the Indian Institute of Technology, Delhi, India, in 2008. His research interests include HVDC and Power Systems.