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A Support Vector Machine Learning-Based Protection Technique for MT-HVDC Systems

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  • Raheel Muzzammel

    (Department of Electrical Engineering, University of Lahore, Lahore 54000, Pakistan)

  • Ali Raza

    (Department of Electrical Engineering, University of Lahore, Lahore 54000, Pakistan)

Abstract

High voltage direct current (HVDC) transmission systems are suitable for power transfer to meet the increasing demands of bulk energy and encourage interconnected power systems to incorporate renewable energy sources without any fear of loss of synchronism, reliability, and efficiency. The main challenge associated with DC grid protection is the timely diagnosis of DC faults because of its rapid built up, resulting in failures of power electronic circuitries. Therefore, the demolition of HVDC systems is evaded by identification, classification, and location of DC faults within milliseconds (ms). In this research, the support vector machine (SVM)-based protection algorithm is developed so that DC faults could be identified, classified, and located in multi-terminal high voltage direct current (MT-HVDC) systems. A four-terminal HVDC system is developed in Matlab/Simulink for the analysis of DC voltages and currents. Pole to ground and pole to pole faults are applied at different locations and times. Principal component analysis (PCA) is used to extract reduced dimensional features. These features are employed for the training and testing of SVM. It is found from simulations that DC faults are identified, classified, and located within 0.15 ms, ensuring speedy DC grid protection. The realization and practicality of the proposed machine learning algorithm are demonstrated by analyzing more straightforward computations of standard deviation and normalization.

Suggested Citation

  • Raheel Muzzammel & Ali Raza, 2020. "A Support Vector Machine Learning-Based Protection Technique for MT-HVDC Systems," Energies, MDPI, vol. 13(24), pages 1-33, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6668-:d:463706
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    References listed on IDEAS

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    1. Van Hertem, Dirk & Ghandhari, Mehrdad, 2010. "Multi-terminal VSC HVDC for the European supergrid: Obstacles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3156-3163, December.
    2. Raheel Muzzammel, 2019. "Traveling Waves-Based Method for Fault Estimation in HVDC Transmission System," Energies, MDPI, vol. 12(19), pages 1-31, September.
    3. Blond, S. Le & Bertho, R. & Coury, D.V. & Vieira, J.C.M., 2016. "Design of protection schemes for multi-terminal HVDC systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 965-974.
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    Cited by:

    1. Raheel Muzzammel & Rabia Arshad & Ali Raza & Nebras Sobahi & Umar Alqasemi, 2023. "Two Terminal Instantaneous Power-Based Fault Classification and Location Techniques for Transmission Lines," Sustainability, MDPI, vol. 15(1), pages 1-24, January.
    2. Abha Pragati & Manohar Mishra & Pravat Kumar Rout & Debadatta Amaresh Gadanayak & Shazia Hasan & B. Rajanarayan Prusty, 2023. "A Comprehensive Survey of HVDC Protection System: Fault Analysis, Methodology, Issues, Challenges, and Future Perspective," Energies, MDPI, vol. 16(11), pages 1-39, May.
    3. Sahebkar Farkhani, Jalal & Çelik, Özgür & Ma, Kaiqi & Bak, Claus Leth & Chen, Zhe, 2024. "A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).

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