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Restricted Boltzmann Machines Based Fault Estimation in Multi Terminal HVDC Transmission System

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Intelligent Technologies and Applications (INTAP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1198))

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Abstract

The facilitation of bulk power transmission and non-synchronized interconnection of alternating current (AC) grids convince engineers and researchers to explore high voltage direct current (HVDC) transmission system in a comprehensive way. This exploration focuses on control and protection of HVDC transmission system. Fault estimation is a core component of protection of HVDC transmission system. This is because of sudden built up of direct current (DC) fault. In this research, DC fault is estimated in multi terminal HVDC transmission system based on restricted Boltzmann machine. Restricted Boltzmann machine is a generative stochastic artificial neural network in which learning of probability distribution is conducted over the set of inputs. Three terminal HVDC transmission system is simulated under normal and faulty conditions to analyze variations in electrical parameters. These variations serve as learning parameters of restricted Boltzmann machine. Contrastive divergence algorithm is developed to train restricted Boltzmann machine. It is an approximate maximum likelihood learning algorithm in which gradient of difference of divergences is followed. It is found that fault is estimated with the testing of variations in minimum time steps. Simulation environment is built in Matlab/Simulink.

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References

  1. Hingorani, N.G.: High voltage DC transmission: a power electronics workhorse. IEEE Spectr. 33(4), 63–72 (1996)

    Article  Google Scholar 

  2. Ellert, F.J.: HVDC for the long run. Spectrum, 36–42 (1976)

    Google Scholar 

  3. Arrillaga, J.J.: High Voltage Direct Current Transmission. Peter Peregrinus Ltd., Stevenage (1983)

    Google Scholar 

  4. Padyar, K.R.: HVDC Power Transmission Systems. Wiley Eastern, New Delhi (1990)

    Google Scholar 

  5. High Voltage Direct Current Handbook, California Electric Power Research Institute, Palo Alto, California (1994)

    Google Scholar 

  6. Starke, M., Tolbert, L.M., Ozpineci, B.: AC vs. DC distribution: a loss comparison. In: IEEE/PES Transmission and Distribution Conference and Exposition, Chicago, IL, pp. 1–7 (2008)

    Google Scholar 

  7. Sun, T., Xia, J., Sun, Y., Mao, X.: Research on the applicable range of AC and DC transmission voltage class sequence. In: International Conference on Power System Technology, Chengdu, pp. 374–380 (2014)

    Google Scholar 

  8. Meah, K., Ula, S.: Comparative evaluation of HVDC and HVAC transmission systems. In: IEEE Power Engineering Society General Meeting, Tampa, FL, pp. 1–5 (2007)

    Google Scholar 

  9. Uhlmann, E.: Power Transmission by Direct Current. Springer, Heidelberg (1975). https://doi.org/10.1007/978-3-642-66072-6

    Book  Google Scholar 

  10. Bowles, J.P., et al.: AC-DC economics and alternatives-1987 panel session report. IEEE Trans. Power Delivery 5(4), 1241–1248 (1990)

    Google Scholar 

  11. Bateman, L.A., Haywood, R.W.: Nelson river DC transmission project. IEEE Trans. Power Appar. Syst. PAS 88(5), 688–693 (1969)

    Article  Google Scholar 

  12. Halder, T.: Comparative study of HVDC and HVAC for a bulk power transmission. In: International Conference on Power, Energy and Control (ICPEC), Sri Rangalatchum Dindigul, pp. 139–144 (2013)

    Google Scholar 

  13. Ruderval, R., Charpenitier, J.P., Sharma, R.: High voltage direct current transmission systems technology review paper. Energy Week, Washington D.C., USA (2000)

    Google Scholar 

  14. Hammad, A.E., Long, W.F.: Performance and economic comparisons between point-to-point HVDC transmission and hybrid back-to-back HVDC/AC transmission. IEEE Trans. Power Delivery 5(2), 1137–1144 (1990)

    Article  Google Scholar 

  15. Chamia, M.: The role of HVDC transmission in the 21st century. In: IEEE WPM - Panel Session (1999)

    Google Scholar 

  16. Tenzer, M., Koch, H., Imamovic, D.: Underground transmission lines for high power AC and DC transmission. In: IEEE/PES Transmission and Distribution Conference and Exposition (T&D), Dallas, TX, pp. 1–4 (2016)

    Google Scholar 

  17. Long, W.F., Litzenberger, W.: Fundamental concepts in high voltage direct current power transmission PES (T&D), Orlando, FL, pp. 1–2 (2012)

    Google Scholar 

  18. Bahrman, M.P.: Overview of HVDC transmission. IEEE PES Power Systems Conference and Exposition, Atlanta, GA, pp. 18–23 (2006)

    Google Scholar 

  19. Wang, H., Redfern, M.A.: The advantages and disadvantages of using HVDC to interconnect AC networks. In: 45th International Universities Power Engineering Conference (UPEC), pp. 1–5 (2010)

    Google Scholar 

  20. Keim, T., Bindra, A.: Recent advances in HVDC and UHVDC transmission [Happenings]. IEEE Power Electron. Mag. 4(4), 12–18 (2017)

    Article  Google Scholar 

  21. Muzzammel, R., et al.: MT–HVdc systems fault classification and location methods based on traveling and non-traveling waves—a comprehensive review. Appl. Sci. 9, 4760 (2019)

    Article  Google Scholar 

  22. Muzzammel, R.: Traveling waves-based method for fault estimation in HVDC transmission system. Energies 12, 3614 (2019)

    Article  Google Scholar 

  23. Muzzammel, R., Fateh, H.M., Ali, Z.: Analytical behaviour of thyrister based HVDC transmission lines under normal and faulty conditions. In: International Conference on Engineering and Emerging Technologies (ICEET), pp. 1–5, Lahore (2018)

    Google Scholar 

  24. Muzzammel, R.: Machine learning based fault diagnosis in HVDC transmission lines. In: Bajwa, I.S., Kamareddine, F., Costa, A. (eds.) INTAP 2018. CCIS, vol. 932, pp. 496–510. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-6052-7_43

    Chapter  Google Scholar 

  25. Zhang, Y., Tai, N., Xu, B.: Fault analysis and traveling wave protection scheme for bipolar HVDC lines. IEEE Trans. Power Deliv. 27(3), 1583–1591 (2012)

    Article  Google Scholar 

  26. Johnson, J.M., Yadav, A.: Complete protection scheme for fault detection, classification and location estimation in HVDC transmission lines using support vector machines. IET Sci. Meas. Technol. 11(3), 279–287 (2017)

    Article  Google Scholar 

  27. He, Z., Liao, K., Li, X., Lin, S., Yang, J., Mai, R.: Natural frequency based line fault location in HVDC lines. IEEE Trans. Power Deliv. 29(2), 851–859 (2014)

    Article  Google Scholar 

  28. Huai, Q., et al.: Backup protection scheme for multi-terminal HVDC system based on wavelet-packet energy entropy. IEEE Access 7, 49790–49803 (2019)

    Article  Google Scholar 

  29. Leterme, W., Azad, S.P., Van Hertem, D.: HVDC grid protection algorithm design in phase and modal domains. IET Renew. Power Gener. 12(13), 1538–1546 (2018)

    Article  Google Scholar 

  30. Salehi, M., Namdari, F.: Fault classification and faulted phase selection for transmission line using morphological edge detection filter. IET Gener. Transm. Distrib. 12(7), 1595–1605 (2018)

    Google Scholar 

  31. Luo, G., Yao, C., Liu, Y., Tan, Y., He, J., Wang, K.: Stacked auto-encoder based fault location in VSC-HVDC. IEEE Access 6, 33216–33224 (2018)

    Article  Google Scholar 

  32. Hoseinzadeh, B., Amini, M.H., Bak, C.L., Blaabierg, F.: High impedance DC fault detection and localization in HVDC transmission lines using harmonic analysis. In: International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I&CPS Europe, pp. 1–4 (2018)

    Google Scholar 

  33. Lan, S., Chen, M.J., Chen, D.Y.: A novel HVDC double terminal nonsynchronous fault location method based on convolutional neural network. IEEE Trans. Power Deliv. 34(3), 848–857 (2019)

    Article  Google Scholar 

  34. Suonan, J., Gao, S., Song, G.: A novel fault location method for HVDC transmission lines. IEEE Trans. Power Deliv. 25, 1203–1209 (2010)

    Article  Google Scholar 

  35. Nanayakkara, O., Rajapakse, A., Wachal, R.: Travelling wave-based line fault location in star-connected multi-terminal HVDC systems. IEEE Trans. Power Deliv. 27, 2286–2294 (2012)

    Article  Google Scholar 

  36. Dewe, M.B., Sankar, S., Arrillaga, J.: The application of satellite time references to HVDC fault location. IEEE Trans. Power Deliv. 8(3), 1295–1302 (1993)

    Article  Google Scholar 

  37. Li, Y., Zhang, S., Li, H.: A fault location method based on genetic algorithm for high-voltage direct current transmission line. Eur. Trans. Electr. Power 22, 866–878 (2012)

    Article  Google Scholar 

  38. Yuangsheng, L., Gang, W., Haifeng, L.: Time domain fault-location method on HVDC transmission lines under unsynchronized two-end measurement and uncertain line parameters. IEEE Trans. Power Deliv. 30, 1031–1038 (2015)

    Article  Google Scholar 

  39. Livani, H., Evrenosoglu, C.Y.: A single-ended fault location method for segmented HVDC transmission line. Electr. Power Syst. Res. 107, 190–198 (2014)

    Article  Google Scholar 

  40. Guoing, S., Xu, C., Xinlei, C.: A fault location method for VSC-HVDC transmission lines based on natural frequency of current. Electr. Power Energy Syst. 63, 347–352 (2014)

    Article  Google Scholar 

  41. Yusuff, A.A., Jimoh, A.A., Munda, J.L.: Fault location in transmission lines based on stationary wavelet transform determinant function feature and support vector regression. Electr. Power Syst. Res. 110, 73–83 (2014)

    Article  Google Scholar 

  42. Azad, S.P., Hertem, D.V.: A fast local bus current-based primary relaying algorithm for HVDC grids. IEEE Trans. Power Deliv. 32(1), 193–202 (2017)

    Article  Google Scholar 

  43. Bucher, M.K., Franck, C.M.: Fault current interruption in multiterminal HVDC networks. IEEE Trans. Power Deliv. 31(1), 87–95 (2016)

    Article  Google Scholar 

  44. Mokhberdoran, A., Silva, N., Leite, H., Carvalho, A.: Unidirectional protection strategy for multi-terminal HVDC grids. Trans. Environ. Electr. Eng. 1(4), 58–65 (2016)

    Article  Google Scholar 

  45. Leterme, W., Azad, S.P., Hertem, D.V.: A local backup protection algorithm for HVDC grids. IEEE Trans. Power Deliv. 31(4), 1767–1775 (2016)

    Article  Google Scholar 

  46. Hertem, D.V., Ghandhari, M.: Multi-terminal VSC HVDC for the European supergrid: obstacles. Renew. Sustain. Energy Rev. 14(9), 3156–3163 (2010)

    Article  Google Scholar 

  47. Kerf, K.D., et al.: Wavelet-based protection strategy for dc faults in multi-terminal VSC HVDC systems. IET Gen. Transm. Distrib. 5(4), 496–503 (2011)

    Article  Google Scholar 

  48. Leterme, W., Beerten, J., Hertem, D.V.: Non-unit protection of HVDC grids with inductive dc cable termination. IEEE Trans. Power Del. 31(2), 820–828 (2016)

    Article  Google Scholar 

  49. Sneath, J., Rajapakse, A.D.: Fault detection and interruption in an earthed HVDC grid using ROCOV and hybrid dc breakers. IEEE Trans. Power Deliv. 31(3), 973–981 (2016)

    Article  Google Scholar 

  50. Elmore, W.A.: Protective Relaying Theory and Applications. Marcel Dekker, New York (2004)

    Google Scholar 

  51. Naidoo, D., Ijumba, N.: HVDC line protection for the proposed future HVDC systems. In: Proceedings IEEE PowerCon, vol. 2, pp. 1327–1332 (2004)

    Google Scholar 

  52. Sun, J., Saeedifard, M., Meliopoulos, A.P.S.: Backup protection of multi-terminal HVDC grids based on quickest change detection. IEEE Trans. Power Deliv. 34(1), 177–187 (2019)

    Article  Google Scholar 

  53. Farshad, M.: Detection and classification of internal faults in bipolar HVDC transmission lines based on K-means data description method. Int. J. Electr. Power Energy Syst. 104, 615–625 (2019)

    Article  Google Scholar 

  54. Azad, S.P., Leterme, W., Hertem, D.V.: A DC grid primary protection algorithm based on current measurements. In: 17th European Conference on Power Electronics and Applications, EPE 2015 ECCE-Europe, Geneva, pp. 1–10 (2015)

    Google Scholar 

  55. Yang, Q., Blond, S.L., Aggarwal, R., Wang, Y., Li, J.: New ANN method for multi-terminal HVDC protection relaying. Electr. Power Syst. Res. 148, 192–201 (2017)

    Article  Google Scholar 

  56. Augustin, T., Jahn, I., Norrga, S., Nee, H.: Transient behaviour of VSC-HVDC links with DC breakers under faults. In: 19th European Conference on Power Electronics and Applications, EPE 2017 ECCE Europe, Warsaw, pp. P.1–P.10 (2017)

    Google Scholar 

  57. Li, C., Gole, A.M., Zhao, C.: A fast DC fault detection method using DC reactor voltages in HVDC grids. IEEE Trans. Power Deliv. 33(5), 2254–2264 (2018)

    Article  Google Scholar 

  58. Bertho, R., Lacerda, V.A., Monaro, R.M., Vieira, J.C.M., Coury, D.V.: Selective nonunit protection technique for multiterminal VSC HVDC grids. IEEE Trans. Power Deliv. 33(5), 2106–2114 (2018)

    Article  Google Scholar 

  59. Xie, Z., Zou, G., Gao, L., Zhang, J., Gao, H.: Voltage pole-wave protection scheme for multi-terminal DC grid. J. Eng. 2019(16), 806–811 (2019)

    Google Scholar 

  60. Yeap, Y.M., Ukil, A.: Fault detection in HVDC system using short time fourier transform. In: IEEE Power and Energy Society General Meeting, PESGM, Boston, MA, pp. 1–5 (2016)

    Google Scholar 

  61. Brigham, E.O.: The Fast Fourier Transform. Prentice Hall, Englewood Cliffs (1974)

    MATH  Google Scholar 

  62. Vasanth, S., Yeap, Y.M., Ukil, A.: Fault location estimation for VSC-HVDC system using artificial neural network. In: IEEE Region 10 Conference, TENCON, pp. 501–504 (2016)

    Google Scholar 

  63. Elgeziry, M.Z., Elsadd, M.A., Elkalashy, N.I., Kawady, T.A., Taalab, A.M.I.: AC spectrum analysis for detecting DC faults on HVDC systems. In: 19th International Middle East Power Systems Conference, MEPCON, pp. 708–715 (2017)

    Google Scholar 

  64. Satpathi, K., Yeap, Y.M., Ukil, A., Geddada, N.: Short-time Fourier Transform based transient analysis of VSC interfaced point-to-point dc system. IEEE Trans. Industr. Electron. 65(5), 4080–4091 (2018)

    Article  Google Scholar 

  65. Ukil, A., Yeap, Y.M., Satpathi, K., Geddada, N.: Fault identification in AC and DC systems using STFT analysis of high frequency components. In: IEEE Conference on Innovative Smart Grid Technologies – Asia, ISGT-Asia, pp. 1–6 (2017)

    Google Scholar 

  66. Gaouda, A.M., El-Saadany, E.F., Salama, M.M.A., Sood, V.K., Chikhani, A.Y.: Monitoring HVDC systems using wavelet multi-resolution analysis. IEEE Trans. Power Syst. 16(4), 662–670 (2001)

    Article  Google Scholar 

  67. Murthy, P.K., Amarnath, J., Kamakshiah, S., Singh, B.P.: Wavelet transform approach for detection and location of faults in HVDC system. In: IEEE Region 10 and the Third international Conference on Industrial and Information Systems, Kharagpur, pp. 1–6 (2008)

    Google Scholar 

  68. Wang, G., Wu, M., Li, H., Hong, C.: Transient based protection for HVDC lines using wavelet-multiresolution signal decomposition. In: Proceedings IEEE/Power Engineering Society Transmission and Distribution Conference, Asia Pacific, pp. 1–4 (2005)

    Google Scholar 

  69. Cai, X., Song, G., Gao, S.: A novel fault-location method for VSC-HVDC transmission lines based on natural frequency of current. Proc. CSEE 28(31), 112–119 (2011)

    Google Scholar 

  70. Liu, X., Osman, A.H., Malik, O.P.: Hybrid traveling wave/boundary protection for monopolar HVDC line. IEEE Trans. Power Deliv. 24(2), 569–578 (2009)

    Article  Google Scholar 

  71. Yang, Y., Tai, N., Fan, C., Yang, L., Chen, S.: Resonance frequency-based protection scheme for ultra-high-voltage direct-current transmission lines. IET Gener. Transm. Distrib. 12(2), 318–327 (2018)

    Article  Google Scholar 

  72. Liu, J., Fan, C., Tai, N.: A novel pilot directional protection scheme for HVDC transmission line based on specific frequency current. In: International conference on Power System Technology, POWERCON, pp. 976–982 (2014)

    Google Scholar 

  73. Cheng, J., Guan, M., Tang, L.V., Huang, H.: A fault location criterion for MTDC transmission lines using transient current characteristics. Int. J. Electr. Power Energy Syst. 61, 647–655 (2014)

    Article  Google Scholar 

  74. Wang, D., Gao, H.L., Luo, S.B., Zou, G.B.: Travelling wave pilot protection for LCC-HVDC transmission lines based on electronic transformers differential output characteristic. Int. J. Electr. Power Energy Syst. 93, 283 (2017)

    Article  Google Scholar 

  75. Farshad, M., Sadeh, J.: A novel fault-location method for HVDC transmission lines based on similarity measure of voltage signals. IEEE Trans. Power Deliv. 28(4), 2483–2490 (2013)

    Article  Google Scholar 

  76. Jana, S., De, A.: A novel zone division approach for power system fault detection using ANN-based pattern recognition technique. Can. J. Electr. Comput. Eng. 40(4), 275–283 (2017)

    Google Scholar 

  77. Wang, Y., Hao, Z., Zhang, B., Kong, F.: A pilot protection scheme for transmission lines in VSC-HVDC grid based on similarity measure of traveling waves. IEEE Access 7, 7147–7158 (2019)

    Article  Google Scholar 

  78. Santos, R.C., Blond, S.L., Coury, D.V., Aggarwal, R.K.: A novel and comprehensive single terminal ANN based decision support for relaying of VSC based HVDC links. Electr. Power Syst. Res. 141, 333 (2016)

    Article  Google Scholar 

  79. Tzelepis, D., Dyśko, A., Fusiek, G., Niewczas, P., Mirsaeidi, S., Booth, C., Dong, X.: Advanced fault location in MTDC networks utilizing optically-multiplexed current measurements and machine learning approach. Int. J. Electr. Power Energy Syst. 97, 319 (2018)

    Article  Google Scholar 

  80. Liu, X., Wei, W., Yu, F.: SVM theory and its application in fault diagnosis of HVDC system. In: 3rd International Conference on Natural Computation, ICNC 2007, Haikou, pp. 665–669 (2007)

    Google Scholar 

  81. Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2(3), 1–27 (2011)

    Article  Google Scholar 

  82. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)

    Article  MATH  Google Scholar 

  83. Tuv, E.: Ensemble learning. In: Guyon, I., Nikravesh, M., Gunn, S., Zadeh, L.A. (eds.) Feature Extraction: Foundations and Applications, pp. 187–204. Springer, Heidelberg (2006). https://doi.org/10.1007/978-3-540-35488-8_8

    Chapter  Google Scholar 

  84. Robnik-Šikonja, M., Kononenko, I.: Theoretical and empirical analysis of ReliefF and RReliefF. Mach. Learn. 53(1), 23–69 (2003)

    Article  MATH  Google Scholar 

  85. Abdelgayed, T.S., Morsi, W.G., Sidhu, T.S.: Fault detection and classification based on co-training of semi supervised machine learning. IEEE Trans. Industr. Electron. 65(2), 1595–1605 (2018)

    Article  Google Scholar 

  86. Jarrahi, M.A., Samet, H., Ghanbari, T.: Fast current-only based fault detection method in transmission line. IEEE Syst. J. 13(2), 1725–1736 (2019)

    Article  Google Scholar 

  87. Chen, M., Lan, S., Chen, D.: Machine learning based one-terminal fault areas detection in HVDC transmission system. In: 8th International Conference on Power and Energy Systems, ICPES, Colombo, Sri Lanka, pp. 278–282 (2018)

    Google Scholar 

  88. Padiyar, K.R., Prabhu, N.: Modelling, control design and analysis of VSC based HVDC transmission systems. In: International Conference on Power System Technology, PowerCon 2004, vol. 11, pp. 774–779 (2004)

    Google Scholar 

  89. Meier, S.: Novel voltage source converter based HVDC transmission system for offshore wind farms. Department of Electrical Engineering Electrical Machines and Power Electronics, Royal Institute of Technology, Stockholm (2005)

    Google Scholar 

  90. Undeland, N.M.T., Robbins, W.: Power Electronics: Converters, Applications, and Design (2003)

    Google Scholar 

  91. Mohamed, Z.S.A.K., Samir, H., Karim, F.M., Rabie, A.: Performance analysis of a voltage source converter (VSC) based HVDC transmission system under faulted conditions. Leonardo J. Sci., 33–46 (2009)

    Google Scholar 

  92. Ana-Irina Stan, D. I. S.: Control of VSC-based HVDC transmission system for offshore wind power plants. Department of Energy Technology, Aalborg University, Denmark (2010)

    Google Scholar 

  93. Cuiqing, D., et al.: A new control strategy of a VSC-HVDC system for high quality supply of industrial plants. IEEE Trans. Power Deliv. 22, 2386–2394 (2007)

    Google Scholar 

  94. Bajracharya, C.: Control of VSC-HVDC for wind power. Master of Science in Energy and Environment, Department of Electrical Power Engineering, Norwegian University of Science and Technology, Trondheim (2008)

    Google Scholar 

  95. De Oliveira Filho, M.E., et al.: A control method for voltage source inverter without dc link capacitor. In Power Electronics Specialists Conference, pp. 4432–4437 (2008)

    Google Scholar 

  96. Machaba, M.B.M.: Explicit damping factor specification in symmetrical optimum tuning of PI controllers. In: 1st African Control Conference, Cape Town, South Africa (2003)

    Google Scholar 

  97. Namho, H., et al.: Fast dynamic DC-link power balancing scheme for a PWM converter inverter system. Proc. Ind. Electron. Soc. 2, 767–772 (1999)

    Google Scholar 

  98. Salakhutdinov, R., Mnih, A., Hinton, G.: Restricted Boltzmann machines for collaborative filtering. In: Proceedings of the 24th International Conference on Machine Learning, ACM 2007 (2007)

    Google Scholar 

  99. Mobahi, H., Collobert, R. (eds.): Deep learning from temporal coherence in video. In: International Conference on Machine Learning, ACM 09, Canada (2009)

    Google Scholar 

  100. Larochelle, H., Bengio, Y. (eds.): Classification using discriminative restricted Boltzmann machines. In: Proceedings of the 25th International Conference on Machine Learning, ACM 2008, Helsinki, Finland (2008)

    Google Scholar 

  101. Larochelle, H., Mandel, M.I. (eds.): Learning algorithms for the classification restricted Boltzmann machine. J. Mach. Learn. Res. 13, 643–669 (2012)

    Google Scholar 

  102. Bengio, Y.: Foundations and trends in machine learning 2, 1–127 (2009)

    Article  Google Scholar 

  103. Lei, Y., Jia, F., Lin, J., Xing, S., Ding, S.X.: An intelligent fault diagnosis method using unsupervised feature learning towards mechanical big data. IEEE Trans. Industr. Electron. 63(5), 3137–3147 (2016)

    Article  Google Scholar 

  104. Wong, K.P.: Artificial intelligence and neural network applications in power systems. In: 2nd International Conference on Advances in Power System Control, Operation and Management, APSCOM 1993, vol. 1, Hong Kong, pp. 37–46 (1993)

    Google Scholar 

  105. Hinton, G.E.: Training products of experts by minimizing contrastive divergence. J. Neural Comput. 14(8), 1771–1800 (2002)

    Article  MATH  Google Scholar 

  106. Fischer, A., Igel, C.: Bounding the bias of contrastive divergence learning. Neural Comput. 23(3), 664–673 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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  1. Department of Electrical Engineering, University of Lahore, Lahore, Pakistan

    Raheel Muzzammel

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  1. Islamia University of Bahawalpur, Baghdad, Pakistan

    Imran Sarwar Bajwa

  2. Metropolitan University, Belgrade, Serbia

    Tatjana Sibalija

  3. University of Technology Malaysia, Johor Bahru, Malaysia

    Dayang Norhayati Abang Jawawi

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Muzzammel, R. (2020). Restricted Boltzmann Machines Based Fault Estimation in Multi Terminal HVDC Transmission System. In: Bajwa, I., Sibalija, T., Jawawi, D. (eds) Intelligent Technologies and Applications. INTAP 2019. Communications in Computer and Information Science, vol 1198. Springer, Singapore. https://doi.org/10.1007/978-981-15-5232-8_66

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