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Electrical fault tolerance of photovoltaic array configurations: Experimental investigation, performance analysis, monitoring and detection

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  • Satpathy, Priya Ranjan
  • Aljafari, Belqasem
  • Thanikanti, Sudhakar Babu
  • Madeti, Siva Rama Krishna

Abstract

The array configurations have gained a higher prominence and application in the solar PV system for reducing power losses during partial shading. However, additional wires can increase the vulnerability of these configurations to electrical faults affecting the performance and lifespan of the modules. Hence, this paper investigates the reliability of these configurations under various electrical faults in the MATLAB and prototype experiment platforms. Additionally, a powerline communication-based PV monitoring system along with fault detection through optimal sensors placement and a user-friendly web application are developed to monitor the performance, detect the presence of the fault and access the data during normal and faulty operation of the PV array respectively. The investigation is conducted for 3x3 array configurations, compared using power curves, and electrical parameters, and the performance along with detection is studied using the real-time data from the proposed monitoring system under normal and faulty conditions. From the analysis, the series-parallel has a higher average tolerance of 59.48% and 48.38% than honeycomb (54.16% and 47.43%), bridge-linked (52.56% and 43.96%), and total-cross-tied (53.66% and 37.48%). The proposed low-cost PV monitoring system has effectively monitored the system performance and is capable of detecting various types of faults in PV arrays and notifying the system with an alarm for proper diagnosis.

Suggested Citation

  • Satpathy, Priya Ranjan & Aljafari, Belqasem & Thanikanti, Sudhakar Babu & Madeti, Siva Rama Krishna, 2023. "Electrical fault tolerance of photovoltaic array configurations: Experimental investigation, performance analysis, monitoring and detection," Renewable Energy, Elsevier, vol. 206(C), pages 960-981.
    • Handle: RePEc:eee:renene:v:206:y:2023:i:c:p:960-981
    DOI: 10.1016/j.renene.2023.02.103
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    References listed on IDEAS

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    1. Satpathy, Priya Ranjan & Jena, Sasmita & Sharma, Renu, 2018. "Power enhancement from partially shaded modules of solar PV arrays through various interconnections among modules," Energy, Elsevier, vol. 144(C), pages 839-850.
    2. Pillai, Dhanup S. & Rajasekar, N., 2018. "A comprehensive review on protection challenges and fault diagnosis in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 18-40.
    3. Yadav, Anurag Singh & Mukherjee, V., 2021. "Conventional and advanced PV array configurations to extract maximum power under partial shading conditions: A review," Renewable Energy, Elsevier, vol. 178(C), pages 977-1005.
    4. Li, B. & Delpha, C. & Diallo, D. & Migan-Dubois, A., 2021. "Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. Colli, Alessandra, 2015. "Failure mode and effect analysis for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 804-809.
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    1. Liu, Yang & Sun, Kangwen & Lv, Mingyun, 2024. "Mission-oriented dynamic reconfiguration of airborne photovoltaic array based on multidisciplinary model," Renewable Energy, Elsevier, vol. 234(C).

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