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Kohzadipour, Mohamad, Valizadeh, Majid, Daniar, Sabah, Khosravi Sarvenoee, Amirhosein. (1405). A New Fast and Accurate Method Based on Fourier Transform for Fault Detection in DC Microgrids. سامانه مدیریت نشریات علمی, 14(3), 198-208. doi: 10.22098/joape.2025.15858.2218
Mohamad Kohzadipour; Majid Valizadeh; Sabah Daniar; Amirhosein Khosravi Sarvenoee. "A New Fast and Accurate Method Based on Fourier Transform for Fault Detection in DC Microgrids". سامانه مدیریت نشریات علمی, 14, 3, 1405, 198-208. doi: 10.22098/joape.2025.15858.2218
Kohzadipour, Mohamad, Valizadeh, Majid, Daniar, Sabah, Khosravi Sarvenoee, Amirhosein. (1405). 'A New Fast and Accurate Method Based on Fourier Transform for Fault Detection in DC Microgrids', سامانه مدیریت نشریات علمی, 14(3), pp. 198-208. doi: 10.22098/joape.2025.15858.2218
Kohzadipour, Mohamad, Valizadeh, Majid, Daniar, Sabah, Khosravi Sarvenoee, Amirhosein. A New Fast and Accurate Method Based on Fourier Transform for Fault Detection in DC Microgrids. سامانه مدیریت نشریات علمی, 1405; 14(3): 198-208. doi: 10.22098/joape.2025.15858.2218

A New Fast and Accurate Method Based on Fourier Transform for Fault Detection in DC Microgrids

Journal of Operation and Automation in Power Engineering
مقاله 5، دوره 14، شماره 3، آبان 2026، صفحه 198-208    اصل مقاله (5.14 M)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2025.15858.2218
نویسندگان
Mohamad Kohzadipour؛ Majid Valizadeh* ؛ Sabah Daniar؛ Amirhosein Khosravi Sarvenoee
Department of Electrical Engineering, Ilam University, Ilam, Iran.
چکیده
This paper utilizes the Fast Fourier Transform (FFT) technique to extract the apparent power of DC microgrids for fault detection. The proposed method separates the real and imaginary components of power and compares the imaginary part with a predetermined threshold. To determine the relay threshold, PP and PG faults are simulated at various distances along each line connected to each bus. The Inverse Fast Fourier Transform (IFFT) is then calculated for each fault at each line and location. The relay threshold is selected based on the lowest significant value among the highest IFFT values calculated for all microgrid lines. This study proposes a novel relay threshold calculation approach, enabling precise fault detection and localization in DC microgrids. The relay threshold value is calculated at the control center and then sent to the microgrid relays. Fault detection is achieved by comparing the IFFT values obtained within the microgrid with the relay threshold value. Once the relay threshold is surpassed, the microgrid detects the fault and promptly sends a trip signal to the circuit breaker. This fault detection strategy accurately identifies the fault location by measuring the current and voltage between the terminals of the faulty section. The proposed method swiftly detects all PP and PG faults (including HIF up to 50 ohms) in grid-connected and islanded modes within 2-3 milliseconds. It accurately locates faults with minimal deviation across various positions. Rigorous simulations using MATLAB and EMTP-RV programs confirm the effectiveness of the protection scheme, emphasizing its reliable performance.
کلیدواژه‌ها
DC microgrid؛ energy threshold؛ fault detection؛ fault location؛ inverse fast fourier transform؛ protection
مراجع
  1. F. S. Al-Ismail, “Dc microgrid planning, operation, and control: A comprehensive review,” IEEE Access, vol. 9, pp. 36154–36172, 2021.
  2. M. Zolfaghari, G. B. Gharehpetian, M. Shafie-khah, and J. P. Catalão, “Comprehensive review on the strategies for controlling the interconnection of ac and dc microgrids,” Int. J. Electr. Power Energy Syst., vol. 136, p. 107742, 2022.
  3. V. F. Pires, A. Pires, and A. Cordeiro, “Dc microgrids: benefits, architectures, perspectives and challenges,” Energies, vol. 16, no. 3, p. 1217, 2023.
  4. M. Shirkhani, J. Tavoosi, S. Danyali, A. K. Sarvenoee, A. Abdali, A. Mohammadzadeh, and C. Zhang, “A review on microgrid decentralized energy/voltage control structures and methods,” Energy Rep., vol. 10, pp. 368–380, 2023.
  5. M. Mola, A. Afshar, N. Meskin, and M. Karrari, “Distributed fast fault detection in dc microgrids,” IEEE Syst. J., vol. 16, no. 1, pp. 440–451, 2020.
  6. Z. Ali, Y. Terriche, S. Z. Abbas, M. A. Hassan, M. Sadiq, C.-L. Su, and J. M. Guerrero, “Fault management in dc microgrids: A review of challenges, countermeasures, and future research trends,” IEEE Access, vol. 9, pp. 128032– 128054, 2021.
  7. B. Zareinia, A. R. Ghiasi, and M. A. Badamchizadeh, “A new integrated fault detection and control scheme of islanded dc microgrids: A resilient approach,” ISA Trans., vol. 146, pp. 165–174, 2024.
  8. A. Deb and A. K. Jain, “An effective data-driven machine learning hybrid approach for fault detection and classification in a standalone low-voltage dc microgrid,” Electr. Eng., 2024.
  9. I. Grcic, H. Pandzic, and D. Novosel, “Fault detection in dc microgrids using short-time fourier transform,” Energies, vol. 14, no. 2, p. 277, 2021.
  10. A. H. Poursaeed and F. Namdari, “High-speed algorithm for fault detection and location in dc microgrids based on a novel time–frequency analysis,” IET Gener. Transm. Distrib., 2024.
  11. N.-C. Yang and J.-M. Yang, “Fault classification in distribution systems using deep learning with data preprocessing methods based on fast dynamic time warping and short-time fourier transform,” IEEE Access, vol. 11, pp. 63612–63622, 2023.
  12. A. Ezzat, B. E. Elnaghi, and A. A. Abdelsalam, “Microgrids islanding detection using fourier transform and machine learning algorithm,” Electr. Power Syst. Res., vol. 196, p. 107224, 2021.
  13. D. K. Asl, A. Hamedi, M. Shadaei, H. Samet, and T. Ghanbari, “A non-iterative method based on fast fourier transform and least square for fault locating in dc microgrids,” in 2020 IEEE Int. Conf. Environ. Electr. Eng., pp. 1–5, IEEE, 2020.
  14. A. R. Aqamohammadi, T. Niknam, S. Shojaeiyan, P. Siano, and M. Dehghani, “Deep neural network with hilbert–huang transform for smart fault detection in microgrid,” Electron., vol. 12, no. 3, p. 499, 2023.
  15. A. Cano, P. Arévalo, D. Benavides, and F. Jurado, “Integrating discrete wavelet transform with neural networks and machine learning for fault detection in microgrids,” Int. J. Electr. Power Energy Syst., vol. 155, p. 109616, 2024.
  16. M. Zakir, A. Arshad, H. A. Sher, and A. Al-Durra, “Design and implementation of a fault detection method for a pv-fed dc-microgrid with power control mechanism,” IET Electr. Power Appl., vol. 16, no. 9, pp. 1057–1071, 2022.
  17. H. L. Dang, S. Kwak, and S. Choi, “Advanced learning technique based on feature differences of moving intervals for detecting dc series arc failures,” Mach., vol. 12, no. 3,
    p. 167, 2024.
  18. R. Montoya, B. P. Poudel, A. Bidram, and M. J. Reno, “Dc microgrid fault detection using multiresolution analysis of traveling waves,” Int. J. Electr. Power Energy Syst., vol. 135, p. 107590, 2022.
  19. N. Bayati, H. R. Baghaee, A. Hajizadeh, M. Soltani, and Z. Lin, “Mathematical morphology-based local fault detection in dc microgrid clusters,” Electr. Power Syst. Res., vol. 192, p. 106981, 2021.
  20. G. K. Rao and P. Jena, “Fault detection in dc microgrid based on the resistance estimation,” IEEE Syst. J., vol. 16, no. 1, pp. 1009–1020, 2021.
  21. N. Bayati, H. R. Baghaee, M. Savaghebi, A. Hajizadeh, M. Soltani, and Z. Lin, “Emd/ht-based local fault detection in dc microgrid clusters,” IET Smart Grid, vol. 5, no. 3, pp. 177–188, 2022.
  22. E. N. Prasad and P. K. Dash, “Fault analysis in photovoltaic generation based dc microgrid using multifractal detrended fluctuation analysis,” Int. Trans. Electr. Energy Syst., vol. 31, no. 1, p. e12564, 2021.
  23. R. Peña-Alzola, M. Sztykiel, C. E. Jones, P. J. Norman, G. Moore, J. Pou, and G. M. Burt, “First-fault detection in dc distribution with it grounding based on sliding discrete fourier-transform,” IEEE Trans. Power Electron., vol. 36, no. 4, pp. 3649–3654, 2020.
  24. S. Salehimehr, S. M. Miraftabzadeh, and M. Brenna, “A novel machine learning-based approach for fault detection and location in low-voltage dc microgrids,” Sustainability, vol. 16, no. 7, p. 2821, 2024.
  25. [25]    M. Ahmadipour, M. M. Othman, R. Bo, Z. Salam, H. M. Ridha, and K. Hasan, “A novel microgrid fault detection and classification method using maximal overlap discrete wavelet packet transform and an augmented lagrangian particle swarm optimization-support vector machine,” Energy Rep., vol. 8, pp. 4854–4870, 2022.
  26. L. Kong and H. Nian, “Fault detection and location method for mesh-type dc microgrid using pearson correlation coefficient,” IEEE Trans. Power Deliv., vol. 36, no. 3, pp. 1428–1439, 2020.
  27. Z. Rafiee, S. Hajiaghasi, M. Rafiee, and A. Salemnia, “A new method for analysis and estimation of microgrid signals under fault conditions,” J. Control Autom. Electr. Syst., vol. 32, pp. 1099–1110, 2021.
  28. A. Ameli, K. A. Saleh, A. Kirakosyan, E. F. El-Saadany, and M. M. Salama, “An intrusion detection method for line current differential relays in medium-voltage dc microgrids,” IEEE Trans. Inf. Forensics Secur., vol. 15, pp. 3580–3594, 2020.
  29. Y. Xia, F. Yu, X. Xiong, Q. Huang, and Q. Zhou, “A novel microgrid islanding detection algorithm based on a multifeature improved lstm,” Energies, vol. 15, no. 8, p. 2810, 2022.
  30. E. Igbineweka and S. Chowdhury, “Application of dual-tree complex wavelet transformation in islanding detection for a hybrid ac/dc microgrid with multiple distributed generators,” Energies, vol. 17, no. 20, p. 5133, 2024.
  31. S. K. Prince, S. Affijulla, and G. Panda, “Protection of dc microgrids based on complex power during faults in on/off-grid scenarios,” IEEE Trans. Ind. Appl., vol. 59, no. 1, pp. 244–254, 2022.
  32. P. Chauhan, C. Gupta, and M. Tripathy, “High speed fault detection and localization scheme for low voltage dc microgrid,” Int. J. Electr. Power Energy Syst., vol. 146, p. 108712, 2023.
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