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Analysis of current and voltage indicators in grid connected PV (photovoltaic) systems working in faulty and partial shading conditions

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  • Silvestre, Santiago
  • Kichou, Sofiane
  • Chouder, Aissa
  • Nofuentes, Gustavo
  • Karatepe, Engin

Abstract

To ensure the optimization of the energy generated by grid connected PV (photovoltaic) systems is necessary to plan a strategy of automatic fault detection. The analysis of current and voltage indicators have demonstrated effectiveness in the detection of permanent faults in the PV array in real time as short-circuits or open circuits present in the system. In this paper, the analysis of the evolution of these indicators is focused on the detection of temporary faults due to partial shade on the PV array or disconnection of the inverter in case of grid fluctuations of voltage or frequency to prevent islanding. These situations can be identified by observation of the evolution of both indicators and power losses due to these effects can be evaluated from them. The analysis and experimental validation were carried out in two grid connected PV systems in Spain and Algeria.

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  • Silvestre, Santiago & Kichou, Sofiane & Chouder, Aissa & Nofuentes, Gustavo & Karatepe, Engin, 2015. "Analysis of current and voltage indicators in grid connected PV (photovoltaic) systems working in faulty and partial shading conditions," Energy, Elsevier, vol. 86(C), pages 42-50.
    • Handle: RePEc:eee:energy:v:86:y:2015:i:c:p:42-50
    DOI: 10.1016/j.energy.2015.03.123
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    6. Chen, Zhicong & Wu, Lijun & Cheng, Shuying & Lin, Peijie & Wu, Yue & Lin, Wencheng, 2017. "Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics," Applied Energy, Elsevier, vol. 204(C), pages 912-931.
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    9. Lee, Chung Geun & Shin, Woo Gyun & Lim, Jong Rok & Kang, Gi Hwan & Ju, Young Chul & Hwang, Hye Mi & Chang, Hyo Sik & Ko, Suk Whan, 2021. "Analysis of electrical and thermal characteristics of PV array under mismatching conditions caused by partial shading and short circuit failure of bypass diodes," Energy, Elsevier, vol. 218(C).
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    11. Shen, Yu & He, Zengxiang & Xu, Zhen & Wang, Yiye & Li, Chenxi & Zhang, Jinxia & Zhang, Kanjian & Wei, Haikun, 2022. "Modeling of photovoltaic modules under common shading conditions," Energy, Elsevier, vol. 256(C).
    12. Rehman, Shafiqur & Ahmed, M.A. & Mohamed, Mohand H. & Al-Sulaiman, Fahad A., 2017. "Feasibility study of the grid connected 10MW installed capacity PV power plants in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 319-329.
    13. Silvano Vergura, 2020. "Bollinger Bands Based on Exponential Moving Average for Statistical Monitoring of Multi-Array Photovoltaic Systems," Energies, MDPI, vol. 13(15), pages 1-14, August.
    14. Livera, Andreas & Theristis, Marios & Makrides, George & Georghiou, George E., 2019. "Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems," Renewable Energy, Elsevier, vol. 133(C), pages 126-143.
    15. Das, Saborni & Hazra, Abhik & Basu, Mousumi, 2018. "Metaheuristic optimization based fault diagnosis strategy for solar photovoltaic systems under non-uniform irradiance," Renewable Energy, Elsevier, vol. 118(C), pages 452-467.
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    17. Silvano Vergura, 2018. "Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters," Energies, MDPI, vol. 11(3), pages 1-18, February.

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