آمار

تعداد نشریات32
تعداد شماره‌ها502
تعداد مقالات4,519
تعداد مشاهده مقاله7,978,455
تعداد دریافت فایل اصل مقاله5,364,305
Khodsuz, Masume. (1404). Islanding Detection of Synchronous Generator in Distribution Network Based on Machine Learning Methods. سامانه مدیریت نشریات علمی, 13(3), 231-237. doi: 10.22098/joape.2024.14318.2100
Masume Khodsuz. "Islanding Detection of Synchronous Generator in Distribution Network Based on Machine Learning Methods". سامانه مدیریت نشریات علمی, 13, 3, 1404, 231-237. doi: 10.22098/joape.2024.14318.2100
Khodsuz, Masume. (1404). 'Islanding Detection of Synchronous Generator in Distribution Network Based on Machine Learning Methods', سامانه مدیریت نشریات علمی, 13(3), pp. 231-237. doi: 10.22098/joape.2024.14318.2100
Khodsuz, Masume. Islanding Detection of Synchronous Generator in Distribution Network Based on Machine Learning Methods. سامانه مدیریت نشریات علمی, 1404; 13(3): 231-237. doi: 10.22098/joape.2024.14318.2100

Islanding Detection of Synchronous Generator in Distribution Network Based on Machine Learning Methods

Journal of Operation and Automation in Power Engineering
مقاله 6، دوره 13، شماره 3، 2025، صفحه 231-237    اصل مقاله (852.08 K)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2024.14318.2100
نویسنده
Masume Khodsuz*
Faculty of Electrical and Computer Engineering, University of Science and Technology of Mazandaran, Behshahr, Mazandaran, Iran.
چکیده
In this paper, a novel approach for detecting islanding events in distribution networks special for synchronous generator type is presented. The proposed method leverages information derived from negative sequence voltage components, synchronous generator field voltage, positive sequence impedance variation rate, voltage harmonic distortion factor, and features extracted through wavelet transform applied to voltage waveforms. In order to establish a robust classification system without the necessity of explicit threshold determination, a pattern recognition method is employed. The dataset derived from these characteristics undergoes training using multi-layer support vector machines and a random forest optimization algorithm, resulting in five distinct classes. The study incorporates experimental samples encompassing various scenarios such as symmetric and asymmetric fault occurrences, load variations at different points, capacitor bank switching, variable load switching, nonlinear load switching, and islanding on a modified 34-bus IEEE network. The proposed islanding detection method demonstrates its effectiveness in distinguishing electrical islanding from power quality phenomena such as voltage oscillation, voltage sag, voltage swell, and dynamic voltage changes. Conducted simulations in MATLAB validate the efficacy of the proposed method.
کلیدواژه‌ها
Islanding detection؛ synchronous generator؛ support vector machines؛ rendom forest؛ power quality phenomena
مراجع
  1. Seyedi, S. A. Taher, B. Ganji, and J. Guerrero, “A hybrid islanding detection method based on the rates of changes in voltage and active power for the multi-inverter systems,” IEEE Trans. Smart Grid, vol. 12, no. 4, pp. 2800–2811, 2021.
  2. Hussain, C.-H. Kim, and S. Admasie, “An intelligent islanding detection of distribution networks with synchronous machine dg using ensemble learning and canonical methods,” IET Gener. Transm. Distrib., vol. 15, no. 23, pp. 3242–3255, 2021.
  3. Radmanesh and M. Saeidi, “Stabilizing microgrid frequency by linear controller design to increase dynamic response of diesel generator frequency control loop,” J. Oper. Autom. Power Eng., vol. 7, no. 2, pp. 216–226, 2019.
  4. “Ieee recommended practice for utility interface of photovoltaic (pv) systems,” IEEE Std 929-2000, 2000.
  5. Sepehrirad, R. Ebrahimi, E. Alibeiki, and S. Ranjbar, “Thevenin impedance concept for fast detection of microgrid islanding scenarios in the presence of small synchronous generators,” J. Oper. Autom. Power Eng., vol. 12, no. 2, pp. 91–106, 2024.
  6. Khamis, H. Shareef, E. Bizkevelci, and T. Khatib, “A review of islanding detection techniques for renewable distributed generation systems,” Renewable Sustainable Energy Rev., vol. 28, pp. 483–493, 2013.
  7. Bakhshi-Jafarabadi, J. Sadeh, J. de Jesus Chavez, and M. Popov, “Two-level islanding detection method for gridconnected photovoltaic system-based microgrid with small non-detection zone,” IEEE Trans. Smart Grid, vol. 12, no. 2, pp. 1063–1072, 2020.
  8. Mlakic, H. R. Baghaee, and S. Nikolovski, “A novel anfis-´ based islanding detection for inverter-interfaced microgrids,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 4411–4424, 2018.
  9. C. Vieira, W. Freitas, and D. Salles, “Characteristics of voltage relays for embedded synchronous generators protection,” IET Gener. Transm. Distrib., vol. 1, no. 3, pp. 484–491, 2007.
  10. Pangedaiah, P. S. K. Reddy, Y. Obulesu, V. R. Kota, and M. L. Alghaythi, “A robust passive islanding detection technique with zero-non-detection zone for inverter-interfaced distributed generation,” IEEE Access, vol. 10, pp. 96296– 96306, 2022.
  11. Rostami, H. Abdi, M. Moradi, J. Olamaei, and E. Naderi, “Islanding detection based on rocov and rocorp parameters in the presence of synchronous dg applying the capacitor connection strategy,” Electr. Power Compon. Syst., vol. 45, no. 3, pp. 315–330, 2017.
  12. R. Baghaee, D. Mlakic, S. Nikolovski, and T. Dragicevi´ c,´ “Support vector machine-based islanding and grid fault detection in active distribution networks,” IEEE J. Emerging Sel. Top. Power Electron., vol. 8, no. 3, pp. 2385–2403, 2019.
  13. H. Shah and B. R. Bhalja, “A new rate of change of impedance-based islanding detection scheme in presence of distributed generation,” Electr. Power Compon. Syst., vol. 42, no. 11, pp. 1172–1180, 2014.
  14. Sareen, B. R. Bhalja, and R. P. Maheshwari, “Universal islanding detection technique based on rate of change of sequence components of currents for distributed generations,” IET Renewable Power Gener., vol. 10, no. 2, pp. 228–237, 2016.
  15. Reigosa, F. Briz, C. Blanco, P. García, and J. M. Guerrero, “Active islanding detection for multiple parallel-connected inverter-based distributed generators using high-frequency signal injection,” IEEE Trans. Power Electron., vol. 29, no. 3, pp. 1192–1199, 2013.
  16. K. Choudhury and P. Jena, “A digital lock-in amplifier assisted active islanding detection technique for dc microgrids,” IEEE Trans. Ind. Appl., vol. 59, no. 1, pp. 377–391, 2022.
  17. Velasco, C. Trujillo, G. Garcerá, and E. Figueres, “Review of anti-islanding techniques in distributed generators,” Renewable Sustainable Energy Rev., vol. 14, no. 6, pp. 1608– 1614, 2010.
  18. Mlakic, H. R. Baghaee, and S. Nikolovski, “A novel anfis-´ based islanding detection for inverter-interfaced microgrids,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 4411–4424, 2018.
  19. Kundur, “Power system stability,” Power Syst. Stab. Control, vol. 10, pp. 7–1, 2007.
  20. Chen and Y. Li, “An islanding detection algorithm for inverter-based distributed generation based on reactive power control,” IEEE Trans. Power Electron., vol. 29, no. 9, pp. 4672–4683, 2013.
  21. Laghari, H. Mokhlis, A. H. A. Bakar, M. Karimi, and A. Shahriari, “An intelligent under frequency load shedding scheme for islanded distribution network,” in 2012 IEEE Int. Power Eng. Optim. Conf. Melaka, Malaysia, pp. 40–45, IEEE, 2012.
  22. Karimi, A. Yazdani, and R. Iravani, “Negative-sequence current injection for fast islanding detection of a distributed resource unit,” IEEE Trans. Power Electron., vol. 23, no. 1, pp. 298–307, 2008.
  23. Shi and F. Wu, “An islanding detection algorithm based on fuzzy adaptive phase drift control,” in 2013 IEEE Int. Conf. Inf. Autom. (ICIA), pp. 225–229, IEEE, 2013.
  24. Vahedi and M. Karrari, “Adaptive fuzzy sandia frequencyshift method for islanding protection of inverter-based distributed generation,” IEEE Trans. Power Delivery, vol. 28, no. 1, pp. 84–92, 2012.
  25. Narayanan, S. A. Siddiqui, and M. Fozdar, “Hybrid islanding detection method and priority-based load shedding for distribution networks in the presence of dg units,” IET Gener. Transm. Distrib., vol. 11, no. 3, pp. 586–595, 2017.
  26. A. Laghari, H. Mokhlis, A. Bakar, and M. Karimi, “A new islanding detection technique for multiple mini hydro based on rate of change of reactive power and load connecting strategy,” Energy Convers. Manage., vol. 76, pp. 215–224, 2013.
  27. Ganyun, C. Haozhong, Z. Haibao, and D. Lixin, “Fault diagnosis of power transformer based on multi-layer svm classifier,” Electr. Power Syst. Res., vol. 74, no. 1, pp. 1–7, 2005.
  28. Breiman, “Random forests,” Mach. Learn., vol. 45, pp. 5–32, 2001.
  29. Song, B. Cao, and L. Chang, “A passive islanding detection method for distribution power systems with multiple inverters,” IEEE J. Emerging Sel. Top. Power Electron., vol. 10, no. 5, pp. 5727–5737, 2022.
آمار
تعداد مشاهده مقاله: 819
تعداد دریافت فایل اصل مقاله: 953


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب