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Machine Learning Based Fault Diagnosis in HVDC Transmission Lines

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Intelligent Technologies and Applications (INTAP 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 932))

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Abstract

HVDC transmission system has been becoming an alternating approach to AC transmission because of its stability and effective controlling. Due to revolution in the field of power electronics, it is expected that HVDC transmission system will play a vital role in power transferring in power systems which are becoming more and more complex with the growing demands of load. Therefore, in order to ensure continuity of supply, there is a need to foresee or to detect any abnormality in HVDC systems. Machine learning is a way of acquiring information from data without being explicitly programmed. In this research, fault diagnostic technique is developed based on machine learning approach. Matlab/Simulink will be used to carry out simulation.

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Authors and Affiliations

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

    Raheel Muzzammel

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  1. Raheel Muzzammel
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  1. Department of Computer Science and IT, Islamia University of Bahawalpur, Baghdad, Pakistan

    Imran Sarwar Bajwa

  2. Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

    Fairouz Kamareddine

  3. Department of Computer Engineering and Digital Systems, University of Sao Paulo, São Paulo, Brazil

    Anna Costa

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Muzzammel, R. (2019). Machine Learning Based Fault Diagnosis in HVDC Transmission Lines. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_43

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