Yazar "Ma, Kaiqi" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems
    (Pergamon-Elsevier Science Ltd, 2024) Farkhani, Jalal Sahebkar; Celik, Ozgur; Ma, Kaiqi; Bak, Claus Leth; Chen, Zhe
    High voltage direct current (HVDC) transmission systems represent a significant development for future power systems due to presenting promising solutions for long-distance power transmission. However, the protection of HVDC systems is becoming one of the most significant challenges due to the extremely high short-circuit current within a short time span and the lack of zero crossing in the DC systems. DC protection schemes must detect and isolate the fault within 4-6 ms, while AC protection systems operate with considerably longer response times. Therefore, the techniques utilized for HVDC protection systems require more attention to enhance their performance in the future. This paper provides a comprehensive review of various protection techniques for HVDC systems, highlights recent advances, and analyzes the pros and cons of each method. Initially, different challenges of HVDC protection systems are presented, and then various HVDC protection schemes are discussed and classified into two groups based on the operation time. After that existing protection schemes are investigated in detail by including practical examples. The review aims to close the gap between the presented HVDC protection methods and technical challenges in order to overcome future issues of power system protection. Moreover, signal processing methods and artificial intelligence (AI) techniques, which play a key role in the future of protection systems, are extensively investigated to highlight the possible solutions. Finally, various recommendations, key challenges, and future trends with respect to the development of HVDC protection schemes have been presented for researchers and engineers studying in this field.
  • [ X ]
    Öğe
    VSC MT-HVDC Fault Identification Based on the VMD-TEO and Artificial Neural Network
    (Institute of Electrical and Electronics Engineers Inc., 2023) Farkhani, Jalal S.; Celik, Ozgur; Ma, Kaiqi; Bak, Claus Leth; Chen, Zhe
    This paper presents a single-ended protection scheme based on an artificial neural network (ANN) and a variational mode decomposition (VMD) for the voltage source converter (VSC) multiterminal high voltage DC (MT-HVDC) system. The developed technique depends on the utilization of VMD for feature extraction of measured voltage and current signals which are transferred into the intrinsic mode function (IMF). Then the Teager energy operator (TEO) is applied for tracking the energy content of the IMFs. The energy content of the IMFs is fed into the multilayer perceptron neural network (MLP) neural network for the identification of faults in a test system. The effectiveness of the proposed method is verified on a four-terminal HVDC system with several case studies including high impedance faults (HIFs), and disturbances by using the PSCAD/EMTDC software. The developed ANN-based fault identification method provides promising results in terms of accurate and fast fault detection features. Simulation results verify the accuracy of the proposed protection method for VSC MT-HVDC systems. © 2023 IEEE.