https://orcid.org/0000-0003-3458-6284
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ABSTRACT
The 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%.
Nomenclature
| Abbreviations | = | |
| PV | = | Photovoltaic |
| PV-TE | = | PV-thermometric |
| MC-FDTD | = | Monte Carlo-Finite Difference Time Domain |
| CNT | = | Carbon Nanotube |
| MLPEs | = | Module-Level Power Electronics |
| PERC | = | Passivated Emitter and Rear Cell |
| Al-BSF | = | Aluminum Back Surface Field |
| PID | = | Potential Induced Degradation |
| n-PERT | = | N-Type Passivated Emitter Rear Totally diffused |
| LSC PV | = | luminescent solar concentrator PV |
| c-Si | = | Crystalline silicon |
| PSC | = | partial shading conditions |
| MPP | = | Maximum Power Point |
| MPPT | = | MPP Tracking |
| DMPPT | = | Distributed MPPT |
| BPD | = | Bypass Diode |
| STC | = | standard test conditions |
| SubMICs | = | Submodule Integrated Converters |
| MOSFET | = | Metal-Oxide-Semiconductor Field-Effect Transistor |
| CSD | = | Conduction State Detection |
| IGBT | = | Insulated-Gate Bipolar Transistor |
| NMOS | = | N-channel Metal-oxide Semiconductor |
| PCM | = | phase-changing material |
| TCT | = | Total-Cross-Tied |
| BL | = | Bridge-Link |
| HC | = | Honey Comb |
| SP | = | Series-Parallel |
| PLC | = | Programmable Logic Controller |
| SCU | = | Supervision Control Unit |
| SDKP | = | SuDoKu puzzled |
| IC | = | Incremental Conductance |
| O-TCT | = | Optimal TCT |
| RSP | = | Reconfigurable SP |
| LS-TCT | = | Latin-based puzzle-based TCT |
| M-TCT | = | Modified TCT |
| NS | = | Novel Structure |
| CDV | = | Cross Diagonal View |
| KKSP | = | Ken-Ken Square puzzled |
| WDO | = | Wind-Driven Optimization |
| DE | = | Differential Evolution |
| CS | = | Cuckoo Search |
| SCA | = | Sine-Cosine Algorithm |
| GA | = | Genetic Algorithm |
| HSA | = | Harmony Search Algorithm |
| PSO | = | Particle Swarm Optimization |
| EL-PSO | = | Enhanced Leader-PSO |
| ANN | = | Artificial Neural Network |
| PWM | = | Pulse Width Modulation |
| FSCC | = | Fractional Short Circuit Current |
| EM | = | Electromagnetism-Like Mechanism Algorithm |
| HIT | = | Heterojunction with Intrinsic Thin layer |
| GWO | = | Grey Wolf Optimizer |
| BFO | = | Bacterial Foraging Optimization |
| IGD | = | Improved Gradient Descent |
| GOA | = | Grasshopper Optimization Algorithm |
| P&O | = | Perturb & Observe |
| Symbol | = | |
| VR | = | Reverse Voltage |
| VF | = | Forward (Open Circuit) Voltage |
| VD | = | Forward Voltage Drop |
| I-V | = | Current Voltage |
Disclosure statement
We hereby declare that there is no conflict of interest with regards to this article.
Additional information
Notes on contributors
Nikhil Kushwaha
Nikhil 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 Yadav
Vinod 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 Saha
Radheshyam 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.