Shading fault detection in a grid-connected PV system using vertices principal component analysis
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DOI: 10.1016/j.renene.2020.10.059
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- Ren, Jie & Chen, Xi & Hu, Jian, 2020. "The effect of production- versus consumption-based emission tax under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 219(C), pages 82-98.
- Mellit, A. & Tina, G.M. & Kalogirou, S.A., 2018. "Fault detection and diagnosis methods for photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1-17.
- Harrou, Fouzi & Sun, Ying & Taghezouit, Bilal & Saidi, Ahmed & Hamlati, Mohamed-Elkarim, 2018. "Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches," Renewable Energy, Elsevier, vol. 116(PA), pages 22-37.
- Lamont, Lisa A. & El Chaar, Lana, 2011. "Enhancement of a stand-alone photovoltaic system’s performance: Reduction of soft and hard shading," Renewable Energy, Elsevier, vol. 36(4), pages 1306-1310.
- Song, Qingbin & Wang, Zhishi & Li, Jinhui & Duan, Huabo & Yu, Danfeng & Liu, Gang, 2018. "Comparative life cycle GHG emissions from local electricity generation using heavy oil, natural gas, and MSW incineration in Macau," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2450-2459.
- 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.
- Mohapatra, Alivarani & Nayak, Byamakesh & Das, Priti & Mohanty, Kanungo Barada, 2017. "A review on MPPT techniques of PV system under partial shading condition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 854-867.
- Mansouri, Majdi & Hajji, Mansour & Trabelsi, Mohamed & Harkat, Mohamed Faouzi & Al-khazraji, Ayman & Livera, Andreas & Nounou, Hazem & Nounou, Mohamed, 2018. "An effective statistical fault detection technique for grid connected photovoltaic systems based on an improved generalized likelihood ratio test," Energy, Elsevier, vol. 159(C), pages 842-856.
- Triki-Lahiani, Asma & Bennani-Ben Abdelghani, Afef & Slama-Belkhodja, Ilhem, 2018. "Fault detection and monitoring systems for photovoltaic installations: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2680-2692.
- Maghami, Mohammad Reza & Hizam, Hashim & Gomes, Chandima & Radzi, Mohd Amran & Rezadad, Mohammad Ismael & Hajighorbani, Shahrooz, 2016. "Power loss due to soiling on solar panel: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1307-1316.
- Chine, W. & Mellit, A. & Lughi, V. & Malek, A. & Sulligoi, G. & Massi Pavan, A., 2016. "A novel fault diagnosis technique for photovoltaic systems based on artificial neural networks," Renewable Energy, Elsevier, vol. 90(C), pages 501-512.
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- Zahra Yahyaoui & Mansour Hajji & Majdi Mansouri & Kais Bouzrara, 2023. "One-Class Machine Learning Classifiers-Based Multivariate Feature Extraction for Grid-Connected PV Systems Monitoring under Irradiance Variations," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
- Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
- Abou Houran, Mohamad & Salman Bukhari, Syed M. & Zafar, Muhammad Hamza & Mansoor, Majad & Chen, Wenjie, 2023. "COA-CNN-LSTM: Coati optimization algorithm-based hybrid deep learning model for PV/wind power forecasting in smart grid applications," Applied Energy, Elsevier, vol. 349(C).
- Pillai, Dhanup S. & Shabunko, Veronika & Krishna, Amal, 2022. "A comprehensive review on building integrated photovoltaic systems: Emphasis to technological advancements, outdoor testing, and predictive maintenance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
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Keywords
Photovoltaic system (PV); Partial shading; Fault detection; Fault diagnosis; Principal component analysis (PCA); Interval-valued PCA;All these keywords.
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