Applied Sciences (Jan 2023)

Module-Level Performance Evaluation for a Smart PV System Based on Field Conditions

  • Li Feng,
  • Nowshad Amin,
  • Jingwei Zhang,
  • Kun Ding,
  • Frank U. Hamelmann

DOI
https://doi.org/10.3390/app13031448
Journal volume & issue
Vol. 13, no. 3
p. 1448

Abstract

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This study presents an approach with a simple structure, low complexity and low costs to evaluate the real-time status and localize the faults of a smart PV system at module level based on field conditions. The performance evaluation approach of a PV system is developed through the defined performance indicators, a complex data matrix to track module locations and a thermal model to determine the module temperature. The generalization potential of the proposed approach has been demonstrated through the successful experiment validation. The results show that the performance indicators are greatly corrected by the estimated module temperature with great linear agreement in R2 of 0.922 compared to actual measured temperature under same conditions. Due to the effective performance indicators capturing more performance differences caused by faults of cracks in 0.22 of PV_ΔV, partial shading in 0.47 of PV_ΔV, broken sensors in 0.17 of PI_ΔI and 1 of PV_ΔV separately, the proposed approach is very effective in evaluating the performance of PV modules at module level. Meanwhile, the faulty modules are diagnosed and located through these findings and the data matrix in the smart PV system. Additionally, the sensitivity of the proposed approach to fault in cracks is much higher than that of monitoring only the power.

Keywords