Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Reference :

    1. Chao, K. H., Li, C. J., and Ho, S. H. (2008) Modeling and fault simulation of photovoltaic generation systems using circuit-based model, Proceedings of IEEE International Conference on Sustainable Energy Technologies, pp. 195-202.
    2. Davarifar, M., Rabhi, A., El-Hajjaji, A., Bosche, J. and Pierre, X. (2013) Improved Real Time Amorphous PV Model for Fault Diagnostic Usage, Sustainability in Energy and Buildings, Springer Berlin Heidelberg, pp. 179-188.
    3. Takashima, T, Yamaguchi, J, Otani, K, Oozeki, T, Kato, K and Ishida, M. (2009) Experimental studies of fault location in PV module strings, Solar Energy Material Solar Cells, vol. 93, pp. 1079-82.
    4. Schirone, L, Schirone, L, Califano, FP and Pastena, M. 1994 Fault detection in a photovoltaic plant by time domain reflectometry, Progress in Photovoltaics: Research and Applications. vol. 2, pp. 35-44.
    5. Vergura, S, Acciani, G, Amoruso, V and Patrono, G. (2008) Inferential statistics for monitoring and fault forecasting of PV plants, Proceedings of the IEEE international symposium, industrial electronics, Cambridge, UK. pp. 2414-19.
    6. Drews, A, de Keizer, AC, Beyer, HG, Lorenz, E, Betcke, J and van Sark, WGJHM. (2007) Monitoring and remote failure detection of grid-connected PV systems based on satellite observations, Solar Energy, vol. 81, pp. 548-64.
    7. K-H Chao, S-H Ho, and M-H Wang. (2008) Modeling and fault diagnosis of a photovoltaic system, Electric Power System Research, vol. 78, pp. 97-105.
    8. A. Chouder and S. Silvestre. (2010) Automatic supervision and fault detection of PV systems based on power losses analysis, Energy conversion and management, vol. 51, pp. 1929-1937.
    9. Yue Wu, Zhicong Chen, Lijung Wu, Peijie Lin, Shuying Cheng, and Peimin Lu. (2016) An intelligent fault diagnosis for PV array based on SA-RBF kernel extreme learning machine, Energy Procedia of 8th International Conference on Applied Energy – ICAE2016, pp. 1070-1076.
    10. Strobl, C. and Meckler, P. (2010) Arc Faults in Photovoltaic Systems, Proceedings of the 56th IEEE Holm Conference on Electrical Contacts, pp. 1-7.
    11. Ancuta, F. and Cepisca, C. (2011) Fault analysis possibilities for PV panels, Proceedings of 3rd International Youth Conference, pp. 1-5.
    12. Wendlandt, A. D. S., Buseth, T., Krauter, S. and Grunow, P. (2010) Hot Spot Risk Analysis on Silicon Cell Modules, 25th European Photovoltaic Solar Energy Conference and Exhibition / 5th World Conference on Photovoltaic Energy Conversion, Valencia, Spain, pp. 4002-4006.
    13. Haeberlin, H. and Real, M. (2007) Arc Detector for Remote Detection of Dangerous Arcs on the DC Side of PV Plants, 22nd European Photovoltaic Solar Energy Conference, Milano, Italy, pp. 1-6.
    14. Lee, H. H., Phuong, L. M., Dzung, P. Q., Dan Vu, N. T., and Khoa, L. D. (2010) The new maximum power point tracking algorithm using ANN-based solar PV systems, Proceedings of the IEEE Region 10 Conference (TENCON ’10), Fukuoka, Japan, pp. 2179– 2184.
    15. Roshchupkin, Oleksiy, Smid, Radislav, Kochan, Volodymyr and Sachenko, Anatoly. (2013) Multisensors Signal Processing Using Microcontroller and Neural Networks Identification, Sensors & Transducers Journal, vol.24, no.8, pp. 1-6.
    16. Turchenko, I, Kochan, V. and Sachenko, A. (2007) Accurate Recognition of Multi-Sensor Output Signal Using Modular Neural Networks, International Journal of Information Technology and Intelligent Computing, vol. 2, no. 1, pp. 27- 47.
    17. LAAMAMI, Samah. BENHAMED, Mouna. and SBITA, Lassaad . (2017) Artificial Neural Networkbased Fault Detection and Classification for Photovoltaic System, International Conference on Green Energy Conversion Systems (GECS), pp. 978-984.

Recent Article