[1] Gomes A.D.P.S., Cagil Ozansoy, Anwaar Ulhaq, High sensitivity vegetation high-impedance fault detection based on signal’s high- frequency contents, IEEE Transactions on Power Delivery, vol. 33, no. 3, pp. 1398–1407 (2018), DOI:
10.1109/TPWRD.2018.2791986.
[2] Ghaderi H.L., Ginn I., Mohammadpour H.A., High impedance fault detection: A review, Electric Power Systems Research, vol. 143, pp. 376–388 (2017), DOI:
10.3390/en13236447.
[3] Gautam S., Brahma S.M., Detection of high impedance fault in power distribution systems using mathematical morphology, IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1226–1234 (2013), DOI:
10.1109/TPWRS.2012.2215630.
[4] Sarlak M., Shahrtash S.M., High impedance fault detection using combination of multi-layer perceptron neural networks based on multiresolution morphological gradient features of current waveform, IET Generation, Transmission Distribution, vol. 5, no. 5, pp. 588–595 (2011), DOI:
10.1049/ietgtd.2010.0702.
[5] Ling Liu, Fault detection technology for intelligent boundary switch, Archives of Electrical Engineering, vol. 68, no. 3, pp. 657–666 (2019), DOI:
10.24425/aee.2019.129348.
[6] Milioudis N., Andreou G.T., Labridis D.P., Detection and Location of High Impedance Faults in Multiconductor Overhead Distribution Lines Using Power Line Communication Devices, IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 894–902 (2015), DOI:
10.1109/TSG.2014.2365855.
[7] Chaari O., Meunier M., Brouaye F., Wavelets: A new tool for the resonant grounded power distribution systems relaying, IEEE Trans on Power System Delivery, vol. 12, no. 1, pp. 1–8 (2018), DOI:
10.1109/61.517484.
[8] Mudathir Funsho Akorede, James Katende, Wavelet Transform Based Algorithm for High- Impedance Faults Detection in Distribution Feeders, European Journal of Scientific Research, vol. 41, no. 2, pp. 237–247 (2010).
[9] Douglas G., Cagil O., Anwaar U., High-Sensitivity Vegetation High-Impedance Fault Detection Based on Signal’s High-Frequency Contents, IEEE Transactions on Power Delivery, vol. 33, no. 3, pp. 1398–1407 (2018), DOI:
10.1109/TPWRD.2018.2791986.
[10] Suliman M.Y., A Proposal Technique of High Impedance Fault Detection Using Adaptive Neuro-Fuzzy Logic Control, Engineering and Technology Journal, vol. 34A, no. 11, pp. 2086–2095 (2016).
[11] Girgis A., ChangW., Makram E.B., Analysis of high-impedance fault generated signals using a Kalman filtering approach, IEEE Transactions on Power Delivery, vol. 5, no. 4, pp. 1714–1724 (1990), DOI:
10.1109/61.103666.
[12] Suliman M.Y., Sameer Sadoon Al-Juboori, Design of Fast Real Time Controller for the Dynamic Voltage Restorer Based on Instantaneous Power Theory, International Journal of Energy and Power Engineering, vol. 5, iss. 2:1, pp. 1–6 (2016), DOI:
10.11648/j.ijepe.s.2016050201.11.
[13] Kumar R., Bhim S., Shahani D.T., Chinmay J., Method of earth fault loop impedance measurement without nuisance tripping of RCDs in 3-phase low-voltage circuits, Archives of Electrical Engineering, vol. 26 no. 2, pp. 217–227 (2019), DOI:
10.24425/mms.2019.128350.
[14] Suliman M.Y., Ghazal M., Design and Implementation of Overcurrent Protection Relay, Journal of Electrical Engineering and Technology, vol. 15, pp. 1595–1605 (2020), DOI:
10.1007/s42835-020-00447-0.
[15] Sirojan T., Lu S., Phung B.T., Zhang D., Ambikairajah E., High Impedance Fault Detection by Convolutional Deep Neural Network, IEEE International Conference on High Voltage Engineering and Application (ICHVE), Athens, Greece, pp. 1–4 (2018), DOI:
10.1109/ICHVE.2018.8642080.
[16] Suliman M.Y., Ghazal M.T., Detection of High impedance Fault in Distribution Network Using Fuzzy Logic Control, 2nd International Conference on Electrical, Communication, Computer, Power and Control Engineering (ICECCPCE), Mosul, Iraq, pp. 103–108 (2019), DOI:
10.1109/ICECCPCE46549.2019.203756.
[17] Sekar K., Mohanty N.K., Sahoo A.K., High impedance fault detection using wavelet transform, Technologies for Smart-City, Energy Security and Power, (ICSESP), Bhubaneswar, India, pp. 1–6 (2018), DOI:
10.1109/ICSESP.2018.8376740.
[18] Gabriel de Alvarenga Ferreira, Tatiana Mariano Lessa Assis, A Novel High Impedance Arcing Fault Detection Based on the Discrete Wavelet Transform for Smart Distribution Grids, IEEE PES Innovative Smart Grid Technologies Conference – ISGT, Brazil, pp. 1–6 (2019), DOI:
10.1109/ISGTLA.2019.8895264.
[19] Moloi K., Jordaan J.A., Hamam Y., High impedance fault detection technique based on Discrete Wavelet Transform and support vector machine in power distribution networks, IEEE AFRICON, Cape Town, South Africa, pp. 9–14 (2017), DOI:
10.1109/AFRCON.2017.8095447.
[20] Costa F.B., Souza B.A., Brito N.S.D., Silva J.A.C.B., Santos W.C., Real-Time Detection of Transient Induced by High-Impedance Fault Based on the Boundary Wavelet Transform, IEEE Transaction on Industrial Applications, vol. 51, no. 6, pp. 531–5323 (2015), DOI:
10.1109/TIA.2015.2434993.
[21] ElkalashyN.I., Lehtonen M., Hatem A.D.,Abdel-Maksoud I.T., Mohamed A.I.,DWT-Based Extraction of Residual Currents Throughout Unearthed MV Network For Detecting High Impedance Fault Due to Learning Trees, European Transactions on Electrical Power, ETEP, vol. 17, no. 6, pp. 597–614 (2007), DOI:
10.1002/etep.149.
[22] Yang H., Minyou C., Jinqian Z., High impedance fault identification method of the distribution network based on discrete wavelet transformation, International Conference on Electrical and Control Engineering, Yichang, China, pp. 2262–2265 (2011), DOI:
10.1109/ICECENG.2011.6057329.
[23] Jang J.-S.R., ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man and Cybernetics, vol. 23, no. 3, pp. 665–685 (1993), DOI:
10.1109/21.256541.
[24] Zadeh L., Fuzzy sets, Information and Control, New York, vol. 8, pp. 338–353 (1965), DOI:
10.1016/S0019-9958(65)90241-X.
[25] Werbos P.J., Beyond regression: new tools for prediction and analysis in the behavioural sciences, Ph.D. Thesis, Harvard University, Cambridge, USA (1974).
[26] Mohammed Y. Suliman, Farrag M.E., Bashi S.M., Design of Fast Real Time Controller for the SSSC Based on Takagi-Sugeno (TS) Adaptive Neuro-Fuzzy Control System, International Conference on Renewable Energy and Power Quality, Spain, vol. 1, no. 12, pp. 1025–1030 (2014), DOI:
10.24084/repqj12.575.
[27] Suliman M.Y., Active and reactive power flow management in parallel transmission lines using static series compensation (SSC) with energy storage, International Journal of Electrical and Computer Engineering, vol. 9, no. 6, pp. 4598–4609 (2019), DOI:
10.11591/ijece.v9i6.pp4598-4609.
[28] Mohammed Y. Suliman, Mahmood T. Al-Khayyat, Power flow control in parallel transmission lines based on UPFC, Bulletin of Electrical Engineering and Informatics, vol. 9, no. 5, pp. 1755–1765 (2020), DOI:
10.11591/eei.v9i5.2290.
[29] Banu G., Suja S., Fault location technique using GA-ANFIS for UHV line, Archives of Electrical Engineering, vol. 63, no. 2, pp. 247–262 (2014), DOI:
10.2478/aee-2014-0019.
[30] Al-Khayyat M.T., Suliman M.Y., Neuro Fuzzy based SSSC for Active and Reactive Power Control in AC Lines with Reduced Oscillation, Przeglad Elektrotechniczny, vol. 97, no. 3, pp. 75–79, 2021, DOI:
10.15199/48.2021.03.14.
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