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An I–V characteristic reconstruction-based partial shading diagnosis and quantitative evaluation for photovoltaic strings

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Listed:
  • Zhang, Jingwei
  • Liu, Yongjie
  • Li, Yuanliang
  • Chen, Xiang
  • Ding, Kun
  • Yan, Jun
  • Chen, Xihui

Abstract

The partial shading condition (PSC) is the most common abnormality occurred in photovoltaic (PV) systems. Accurate quantitative evaluation of the shaded area and the severity of the shading is of potential importance in optimizing the maintenance strategy for PV systems. In this paper, we propose a PSC diagnosis and quantitative evaluation method by analyzing the measured string current–voltage (I–V) characteristic obtained from the PV inverter with the I–V scanning function, which includes pre-diagnosis of the system abnormality based on the operational power deviation, the diagnosis of PSCs based on the derivatives characteristics of the PV string, and the quantitative evaluation based on the I–V characteristic reconstruction. The quantitative evaluation of PSCs is the main focus in this paper, where the I–V characteristics of the unshaded PV modules in the partially shaded PV string are reconstructed according to different mismatch levels, respectively. The number of shaded PV modules and the corresponding severity of the partial shadings are estimated according to the reconstructed I–V characteristics. The simulation and experimental results verify that both the proposed diagnosis and quantitative evaluation method is effective with decent accuracy, especially for severe mismatch conditions. Experimental results show that the maximal mean absolute error of the quantified shaded area and quantified shaded rate are approximately 1.4446 units of 1/3 PV modules and 0.026, respectively.

Suggested Citation

  • Zhang, Jingwei & Liu, Yongjie & Li, Yuanliang & Chen, Xiang & Ding, Kun & Yan, Jun & Chen, Xihui, 2024. "An I–V characteristic reconstruction-based partial shading diagnosis and quantitative evaluation for photovoltaic strings," Energy, Elsevier, vol. 300(C).
    • Handle: RePEc:eee:energy:v:300:y:2024:i:c:s0360544224012532
    DOI: 10.1016/j.energy.2024.131480
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    References listed on IDEAS

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    1. Li, Yuanliang & Ding, Kun & Zhang, Jingwei & Chen, Fudong & Chen, Xiang & Wu, Jiabing, 2019. "A fault diagnosis method for photovoltaic arrays based on fault parameters identification," Renewable Energy, Elsevier, vol. 143(C), pages 52-63.
    2. Cavieres, Robinson & Barraza, Rodrigo & Estay, Danilo & Bilbao, José & Valdivia-Lefort, Patricio, 2022. "Automatic soiling and partial shading assessment on PV modules through RGB images analysis," Applied Energy, Elsevier, vol. 306(PA).
    3. Teo, J.C. & Tan, Rodney H.G. & Mok, V.H. & Ramachandaramurthy, Vigna K. & Tan, ChiaKwang, 2020. "Impact of bypass diode forward voltage on maximum power of a photovoltaic system under partial shading conditions," Energy, Elsevier, vol. 191(C).
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