ANN-Based Statistical Computation for Remote End Fault Monitoring of the IEEE 14 Bus Microgrid Network

REFERENCES

• I. Akhtar, and S. Kirmani, “An application of fuzzy fault tree analysis for reliability evaluation of wind energy system,” IETE. J. Res., Vol. 5, no. 1, pp. 15–23, 2020.
   Google Scholar
• P. D. Raval, and A. S. Pandya, “A hybrid PSO-ANN-based fault classification system for EHV transmission lines,” IETE. J. Res., Vol. 1, no. 1, pp. 1–15, 2020.
   Google Scholar
• S. Datta, A. Chattopadhyaya, S. Chattopadhyay, and A. Das, “S-transform based kurtosis analysis for detection of LG and LL faults in 14 Bus microgrid system,” IETE. J. Res., Vol. 2, no. 1, pp. 10–20, 2020.
   Google Scholar
• M. Ikhide, S. B. Tennakoon, H. Ha, A. L. Griffiths, S. Subramanian, and A. J. Adamczyk, “A transient and non-unit-based protection technique for DC grids based on the rate-of-change (R-o-C) of the fault induced travelling wave components,” Sustain. Energy Grid. Netw., Vol. 17, no. 1, pp. 100–11, 2019.
   Google Scholar
• M. Mishra, M. Sahani, and P. K. Rout, “An islanding detection algorithm for distributed generation based on Hilbert–Huang transform and extreme learning machine,” Sustain. Energy Grid. Netw., Vol. 9, no. 1, pp. 13–26, 2017.
   Google Scholar
• A. Ali, Q. A. Khan, and B. Hussain, “Fault modelling and detection in power generation, transmission and distribution systems,” IET. Gener. Transm. Distrib., Vol. 16, no. 3, pp. 2782–91, 2015.
   Google Scholar
• D. Patel, G. N. Chothani, and D. K. Mistry, “Design and development of fault classification algorithm based on relevance vector machine for power transformer,” IET Electr. Power Appl., Vol. 12, no. 4, pp. 557–65, 2018.
   Web of Science ®Google Scholar
• S. Dhar, R. K. Patnaik, and P. K. Dash, “Fault detection and location of photovoltaic based DC microgrid using differential protection strategy,” IEEE Trans. Smart Grid, Vol. 9, no. 5, pp. 4303–12, 2017.
   Web of Science ®Google Scholar
• M. Manohar, E. Koley, and S. Ghosh, “Reliable protection scheme for PV integrated microgrid using an ensemble classifier approach with real-time validation,” IET Sci. Meas. Technol., Vol. 12, no. 2, pp. 200–8, 2017.
   Web of Science ®Google Scholar
• T. Ghanbari, and E. Farjah, “Unidirectional fault current limiter: An efficient interface between the microgrid and main network,” IEEE Trans. Power Syst., Vol. 28, no. 2, pp. 1591–8, 2013.
   Web of Science ®Google Scholar
• B. M. Eid, N. A. Rahim, J. Selvaraj, and A. H. El. Khateb, “Control methods and objectives for electronically coupled distributed energy resources in microgrids,” IEEE Syst. J., Vol. 10, no. 2, pp. 446–52, 2016.
   Web of Science ®Google Scholar
• M. J. Morshed, and A. Sheikh, “A fault – Tolerant control paradigm for microgrid wind energy system,” IEEE Syst. J., Vol. 12, no. 1, pp. 360–72, 2018.
   Web of Science ®Google Scholar
• H. Nademi, L. Vanfretti, and J. Pretlove, “Fault detection method in subsea power distribution systems using statistical optimisation,” IET Energ. Syst. Integ., Vol. 2, no. 2, pp. 144–50, 2020.
   Google Scholar
• A. Heidary, H. Radmanesh, S. H. Naghibi, S. Samandarpour, K. Rouzbehi, and N. Shariati, “Distribution system protection by coordinated fault current limiters,” IET Energ. Syst. Integ., Vol. 2, no. 1, pp. 59–65, 2020.
   Google Scholar
• S. Datta, S. Chattopadhyay, and A. Das, “FFT based harmonic assessment of line to ground fault in 14 bus microgrid system,” in 2017 International Conference on Modelling and Simulation in Science, Technology and Engineering Mathematics (MS-17), Kolkata, India, 2017, pp. 73–86.
   Google Scholar
• S. Datta, A. Chattopadhyaya, S. Chattopadhyay, and A. Das, “Harmonic distortion, inter-harmonic group magnitude and discrete wavelet transformation based statistical parameter estimation for line to ground fault analysis in microgrid system,” in 2020 Micheal Faraday IET International Summit (MFIIS 2020), Kolkata, India, 2020, pp. 177–84.
   Google Scholar
• N. Mukherjee, A. Chattopadhyaya, S. Chattopadhyay, and S. Sengupta, “Discrete-wavelet-transform and stockwell-transform-based statistical parameters estimation for fault analysis in grid-connected wind power system,” IEEE Syst. J., Vol. 14, no. 3, pp. 4320–8, 2020.
   Web of Science ®Google Scholar
• D. Li, A. Ukil, K. Satpathi, and Y. M. Yeap, “Improved S transform-based fault detection method in voltage source converter interfaced DC system,” IEEE Trans. Ind. Electron., Vol. 68, no. 6, pp. 5024–35, 2021.
   Web of Science ®Google Scholar
• M. H. R. A. Syafi, E. Prasetyono, M. K. Khafidli, D. O. Anggriawan, and A. Tjahjono. “Real time series DC arc fault detection based on fast Fourier transform,” in 2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA), Bali, Indonesia, pp. 10–18, 2018.
   Google Scholar
• “Engineering Statistics Handbook”. NIST/SEMATECH e-handbook of statistical methods, NIST, Retrieved 18th March 2012.
   Google Scholar