[صفحه اصلی ]   [Archive] [ English ]  
:: صفحه اصلي :: درباره نشريه :: آخرين شماره :: تمام شماره‌ها :: جستجو :: ثبت نام :: ارسال مقاله :: تماس با ما ::
بخش‌های اصلی
صفحه اصلی::
اطلاعات نشریه::
آرشیو مجله و مقالات::
برای نویسندگان::
برای داوران::
ثبت نام و اشتراک::
صاحب امتیاز::
درباره انجمن::
تماس با ما::
تسهیلات پایگاه::
cope::
metrics::
تعارض منافع::
::
پایگاه های نمایه کننده
..
DOI
کلیک کنید
..
DOR

..
جستجو در پایگاه

جستجوی پیشرفته
..
دریافت اطلاعات پایگاه
نشانی پست الکترونیک خود را برای دریافت اطلاعات و اخبار پایگاه، در کادر زیر وارد کنید.
..
:: دوره 10، شماره 4 - ( 10-1400 ) ::
جلد 10 شماره 4 صفحات 13-1 برگشت به فهرست نسخه ها
تشخیص خطای امپدانس بالا در شبکه‌های توزیع با استفاده از تبدیل فوریه گسسته
زهرا مروج* 1، مهرداد قهرمانی1
1- دانشکده مهندسی برق- دانشگاه سمنان- سمنان- ایران
چکیده:   (2400 مشاهده)
در این مقاله، روشی جدید برای استخراج ویژگی‌های دینامیک برای تشخیص خطای امپدانس بالا با استفاده از تبدیل فوریه گسسته (DFT) ارائه‌شده است. برخلاف روش‌های رایج که از ویژگی‌های استخراج‌شده از پنجره‌های داده پس از بروز خطا برای تشخیص خطای امپدانس بالا استفاده می‌کنند، در روش پیشنهادشده با استفاده از الگوریتم تشخیص بروز اغتشاش در شبکه، از تغییرات نرمال شده ویژگی‌های انتخاب‌شده به‌منظور مقایسه‌ی بین پنجره‌های داده پس از بروز خطا و پیش از بروز خطا، استفاده می‌شود. همچنین با استفاده از پنجره‌های داده پسا-اغتشاش و توسعه یک سیستم تصمیم‌گیری بر اساس خروجی طبقه‌بندی‌کننده SVM و مقایسه مقدار قطعیت رخداد سایر وقایع شبکه با خطای امپدانس بالا، قابلیت اطمینان و امنیت روش پیشنهادی بهبود بخشیده شده است.  روش پیشنهادی بر روی شبکه 34 شینه IEEE در نرم‌افزار EMTP-RV پیاده‌سازی شده است؛ که نتایج حاصل از شبیه‌سازی بیانگر دقت 97/2%، قابلیت اطمینان 98/5% و امنیت 98/8% می‌باشد.
شماره‌ی مقاله: 1
واژه‌های کلیدی: خطای امپدانس بالا، تبدیل فوریه گسسته، تبدیل فوریه سریع، تشخیص اغتشاش، شبکه‎های توزیع، ماشین بردار پشتیبان.
متن کامل [PDF 2354 kb]   (626 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: برق و کامپیوتر
دریافت: 1399/9/18 | پذیرش: 1400/7/10 | انتشار: 1400/9/11
فهرست منابع
1. [1] Gadanayak, D. A. A Review on High-Impedance Ground Fault Detection Techniques in Distribution Networks. Green Technology for Smart City and Society, pp. 299-309.‌2021. [DOI:10.1007/978-981-15-8218-9_26]
2. [2] Tengdin, J., and Westfall, R., "High impedance fault detection technology", Report of PSRC Working Group D15, pp. 1-12, 1996.
3. [3] Benner, C.L., and Russell, B.D., "Practical high-impedance fault detection on distribution feeders", IEEE Trans. Ind. Appl, Vol. 33, No. 3, pp. 635-640, 1997. [DOI:10.1109/28.585852]
4. [4] Mamishev, A. V., Russell, B. D., and Benner, C. L. "Analysis of high impedance faults using fractal techniques", IEEE Trans. Power Syst, vol. 11, no. 1, pp. 435-440, 1996. [DOI:10.1109/59.486130]
5. [5] Ghaderi, A., Ginn III, H.L. and Mohammadpour, H.A., "High impedance fault detection: A review", Electr. Power Syst. Res., Vol. 143, pp. 376-388, 2017. [DOI:10.1016/j.epsr.2016.10.021]
6. [6] Sekar, K., and Mohanty, N.K., "A fuzzy rule base approach for High Impedance Fault detection in distribution system using Morphology Gradient filter", J. King Saud Univ. Eng. Sci, Vol. 32, No. 3, pp. 177-185, 2020. [DOI:10.1016/j.jksues.2018.12.001]
7. [7] Kavaskar. S., and Mohanty, N.K., "Detection of high impedance fault in distribution networks", Ain Shams Engineering Journal, vol. 10, no. 1, pp. 5-13, 2019. [DOI:10.1016/j.asej.2018.04.006]
8. [8] S. Silva, P. Costa, M. Sanatana and D. Leite, "Evolving neuro fuzzy network for real-time high impedance fault detection and classification," Neural Computing and Applications, vol. 32, no. 12, pp. 7597-7610, 2020. [DOI:10.1007/s00521-018-3789-2]
9. [9] Sekar, K., and Mohanty, N.K., "Data mining-based high impedance fault detection using mathematical morphology", Comput. Electr. Eng, Vol. 69, pp. 129-141, 2018. [DOI:10.1016/j.compeleceng.2018.05.010]
10. [10] Aziz, M.A., Hassan, M.M., and Zahab, E.A., "High-impedance faults analysis in distribution networks using an adaptive neuro fuzzy inference system", Electr. Power. Compon. Syst, Vol. 40, No. 11, pp. 1300-1318, 2012. [DOI:10.1080/15325008.2012.689418]
11. [11] Sahoo, S., and Baran, M.E., "A method to detect high impedance faults in distribution feeders", IEEE PES. Trans. Dis. Conf. Exposition, pp. 1-6, 2014. [DOI:10.1109/TDC.2014.6863531]
12. [12] Zhang, S., Xiao, X., and He, Z., "Detection of high‐impedance fault in distribution network based on time-frequency entropy of wavelet transform", IEEJ Trans. Electr. Electron. Eng, Vol. 15, No. 6, pp. 844-853, 2020. [DOI:10.1002/tee.23126]
13. [13] Biswal, M., Ghore, S., Malik, O. P., and Bansal, R. C., "Development of time-frequency based approach to detect high impedance fault in an inverter interfaced distribution system", IEEE Transactions on Power Delivery, Jan. 2021. [DOI:10.1109/TPWRD.2021.3049572]
14. [14] Bhat, A. U. Q., Prakash, A., Tayal, V. K., and Choudekar, P., "High Impedance Fault Analysis of Distributed Power System Network Using Discrete Wavelet Transform", In Advances in Smart Communication and Imaging Systems,Springer, Singapore, pp.561-576, 2021. [DOI:10.1007/978-981-15-9938-5_53]
15. [15] Gadanayak, D.A., and Mallick, R.K., "Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition", Int. J. Electr. Power Energy Syst, Vol. 112, pp. 282-293, 2019. [DOI:10.1016/j.ijepes.2019.04.050]
16. [16] Silva, S., Costa, P., Gouvea, M., Lacerda, A., Alves, F., and Leite, D., "High impedance fault detection in power distribution systems using wavelet transform and evolving neural network", Electr. Power Syst, Vol. 154, pp. 474-483, 2018. [DOI:10.1016/j.epsr.2017.08.039]
17. [17] Moravej, Z., Mortazavi, S.H., and Shahrtash, S.M., "DT‐CWT based event feature extraction for high impedance faults detection in distribution system", Int Trans. Electr. Energ. Syst, Vol. 25, No. 12, pp. 3288-3303, 2015. [DOI:10.1002/etep.2035]
18. [18] Sarlak, M., and Shahrtash, S.M., "High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform", IET. Gener. Transm. Dis, Vol. 5, No. 5, pp. 588 - 595, 2011. [DOI:10.1049/iet-gtd.2010.0702]
19. [19] AsghariGovar. S., Pourghasem. P., and Seyedi. H., "High impedance fault protection scheme for smart grids based on WPT and ELM considering evolving and cross-country faults", Int. J. Electr. Power Energ Syst, vol. 107, pp. 412-421, 2019. [DOI:10.1016/j.ijepes.2018.12.019]
20. [20] Ghaderi, A., Mohammadpour, H.A., Ginn, H.L., and Shin, Y.J., "High-impedance fault detection in the distribution network using the time-frequency-based algorithm", IEEE Trans. Power Delivery., Vol. 30, No. 3, pp. 1260 - 1268, 2015. [DOI:10.1109/TPWRD.2014.2361207]
21. [21] Mortazavi, S.H., Moravej, Z., and Shahrtash, S.M., "A hybrid method for arcing faults detection in large distribution networks", Int. J. Electr. Power Energ Syst, Vol. 94, pp. 141-150, 2018. [DOI:10.1016/j.ijepes.2017.06.036]
22. [22] Mohammadnian, Y., Amraee, T., and Soroudi, A., "Fault detection in distribution networks in presence of distributed generations using a data mining-driven wavelet transform", IET Smart Grid, Vol. 2, No. 2, pp. 163-171, 2019. [DOI:10.1049/iet-stg.2018.0158]
23. [23] Cui, Q., and Weng, Y., "Enhance High Impedance Fault Detection and Location Accuracy via $mu $-PMUs", IEEE Trans. Smart Grid, Vol. 11, No. 1, pp. 797 - 809, 2020. [DOI:10.1109/TSG.2019.2926668]
24. [24] Vapnik. V., and Chervonenkis. A., "The necessary and sufficient conditions for consistency in the empirical risk minimization method", Pattern Recogn Image Anal, vol. 1, no. 3, pp. 283 - 305, 1991.
25. [25] Distribution Test Feeders, IEEE PES Distribution System Analysis Subcommittee's, Distribution Test Feeder Working Group, August 2013.
26. [1] Gadanayak, D. A. A Review on High-Impedance Ground Fault Detection Techniques in Distribution Networks. Green Technology for Smart City and Society, pp. 299-309.‌2021. [DOI:10.1007/978-981-15-8218-9_26]
27. [2] Tengdin, J., and Westfall, R., "High impedance fault detection technology", Report of PSRC Working Group D15, pp. 1-12, 1996.
28. [3] Benner, C.L., and Russell, B.D., "Practical high-impedance fault detection on distribution feeders", IEEE Trans. Ind. Appl, Vol. 33, No. 3, pp. 635-640, 1997. [DOI:10.1109/28.585852]
29. [4] Mamishev, A. V., Russell, B. D., and Benner, C. L. "Analysis of high impedance faults using fractal techniques", IEEE Trans. Power Syst, vol. 11, no. 1, pp. 435-440, 1996. [DOI:10.1109/59.486130]
30. [5] Ghaderi, A., Ginn III, H.L. and Mohammadpour, H.A., "High impedance fault detection: A review", Electr. Power Syst. Res., Vol. 143, pp. 376-388, 2017. [DOI:10.1016/j.epsr.2016.10.021]
31. [6] Sekar, K., and Mohanty, N.K., "A fuzzy rule base approach for High Impedance Fault detection in distribution system using Morphology Gradient filter", J. King Saud Univ. Eng. Sci, Vol. 32, No. 3, pp. 177-185, 2020. [DOI:10.1016/j.jksues.2018.12.001]
32. [7] Kavaskar. S., and Mohanty, N.K., "Detection of high impedance fault in distribution networks", Ain Shams Engineering Journal, vol. 10, no. 1, pp. 5-13, 2019. [DOI:10.1016/j.asej.2018.04.006]
33. [8] S. Silva, P. Costa, M. Sanatana and D. Leite, "Evolving neuro fuzzy network for real-time high impedance fault detection and classification," Neural Computing and Applications, vol. 32, no. 12, pp. 7597-7610, 2020. [DOI:10.1007/s00521-018-3789-2]
34. [9] Sekar, K., and Mohanty, N.K., "Data mining-based high impedance fault detection using mathematical morphology", Comput. Electr. Eng, Vol. 69, pp. 129-141, 2018. [DOI:10.1016/j.compeleceng.2018.05.010]
35. [10] Aziz, M.A., Hassan, M.M., and Zahab, E.A., "High-impedance faults analysis in distribution networks using an adaptive neuro fuzzy inference system", Electr. Power. Compon. Syst, Vol. 40, No. 11, pp. 1300-1318, 2012. [DOI:10.1080/15325008.2012.689418]
36. [11] Sahoo, S., and Baran, M.E., "A method to detect high impedance faults in distribution feeders", IEEE PES. Trans. Dis. Conf. Exposition, pp. 1-6, 2014. [DOI:10.1109/TDC.2014.6863531]
37. [12] Zhang, S., Xiao, X., and He, Z., "Detection of high‐impedance fault in distribution network based on time-frequency entropy of wavelet transform", IEEJ Trans. Electr. Electron. Eng, Vol. 15, No. 6, pp. 844-853, 2020. [DOI:10.1002/tee.23126]
38. [13] Biswal, M., Ghore, S., Malik, O. P., and Bansal, R. C., "Development of time-frequency based approach to detect high impedance fault in an inverter interfaced distribution system", IEEE Transactions on Power Delivery, Jan. 2021. [DOI:10.1109/TPWRD.2021.3049572]
39. [14] Bhat, A. U. Q., Prakash, A., Tayal, V. K., and Choudekar, P., "High Impedance Fault Analysis of Distributed Power System Network Using Discrete Wavelet Transform", In Advances in Smart Communication and Imaging Systems,Springer, Singapore, pp.561-576, 2021. [DOI:10.1007/978-981-15-9938-5_53]
40. [15] Gadanayak, D.A., and Mallick, R.K., "Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition", Int. J. Electr. Power Energy Syst, Vol. 112, pp. 282-293, 2019. [DOI:10.1016/j.ijepes.2019.04.050]
41. [16] Silva, S., Costa, P., Gouvea, M., Lacerda, A., Alves, F., and Leite, D., "High impedance fault detection in power distribution systems using wavelet transform and evolving neural network", Electr. Power Syst, Vol. 154, pp. 474-483, 2018. [DOI:10.1016/j.epsr.2017.08.039]
42. [17] Moravej, Z., Mortazavi, S.H., and Shahrtash, S.M., "DT‐CWT based event feature extraction for high impedance faults detection in distribution system", Int Trans. Electr. Energ. Syst, Vol. 25, No. 12, pp. 3288-3303, 2015. [DOI:10.1002/etep.2035]
43. [18] Sarlak, M., and Shahrtash, S.M., "High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform", IET. Gener. Transm. Dis, Vol. 5, No. 5, pp. 588 - 595, 2011. [DOI:10.1049/iet-gtd.2010.0702]
44. [19] AsghariGovar. S., Pourghasem. P., and Seyedi. H., "High impedance fault protection scheme for smart grids based on WPT and ELM considering evolving and cross-country faults", Int. J. Electr. Power Energ Syst, vol. 107, pp. 412-421, 2019. [DOI:10.1016/j.ijepes.2018.12.019]
45. [20] Ghaderi, A., Mohammadpour, H.A., Ginn, H.L., and Shin, Y.J., "High-impedance fault detection in the distribution network using the time-frequency-based algorithm", IEEE Trans. Power Delivery., Vol. 30, No. 3, pp. 1260 - 1268, 2015. [DOI:10.1109/TPWRD.2014.2361207]
46. [21] Mortazavi, S.H., Moravej, Z., and Shahrtash, S.M., "A hybrid method for arcing faults detection in large distribution networks", Int. J. Electr. Power Energ Syst, Vol. 94, pp. 141-150, 2018. [DOI:10.1016/j.ijepes.2017.06.036]
47. [22] Mohammadnian, Y., Amraee, T., and Soroudi, A., "Fault detection in distribution networks in presence of distributed generations using a data mining-driven wavelet transform", IET Smart Grid, Vol. 2, No. 2, pp. 163-171, 2019. [DOI:10.1049/iet-stg.2018.0158]
48. [23] Cui, Q., and Weng, Y., "Enhance High Impedance Fault Detection and Location Accuracy via $mu $-PMUs", IEEE Trans. Smart Grid, Vol. 11, No. 1, pp. 797 - 809, 2020. [DOI:10.1109/TSG.2019.2926668]
49. [24] Vapnik. V., and Chervonenkis. A., "The necessary and sufficient conditions for consistency in the empirical risk minimization method", Pattern Recogn Image Anal, vol. 1, no. 3, pp. 283 - 305, 1991.
50. [25] Distribution Test Feeders, IEEE PES Distribution System Analysis Subcommittee's, Distribution Test Feeder Working Group, August 2013.


XML   English Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

moravej Z, ghahremani M. Detection of high impedance faults in distribution networks using Discrete Fourier Transform. ieijqp 2022; 10 (4) : 1
URL: http://ieijqp.ir/article-1-797-fa.html

مروج زهرا، قهرمانی مهرداد. تشخیص خطای امپدانس بالا در شبکه‌های توزیع با استفاده از تبدیل فوریه گسسته. نشریه کیفیت و بهره وری صنعت برق ایران. 1400; 10 (4) :1-13

URL: http://ieijqp.ir/article-1-797-fa.html



بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.
دوره 10، شماره 4 - ( 10-1400 ) برگشت به فهرست نسخه ها
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
Persian site map - English site map - Created in 0.07 seconds with 39 queries by YEKTAWEB 4645