IJE TRANSACTIONS B: Applications Vol. 32, No. 2 (February 2019) 242-248    Article in Press

PDF URL: http://www.ije.ir/Vol32/No2/B/9-3008.pdf  
downloaded Downloaded: 54   viewed Viewed: 400

M. Gholami
( Received: October 21, 2018 – Accepted in Revised Form: January 03, 2019 )

Abstract    Due to the increasing need to distributed energy resources in power systems, their problems should be studied. One of the main problem of distributed energy resources is unplanned islanding. The unplanned islanding has some dangers to the power systems and the repairman which are works with the incorrect devices. In this paper, a passive local method is proposed. The proposed method is based on wavelet transform and a new classifier named as wavenet. The wavelet transform is used to extract features from the current waveform of current at the point of common coupling (PCC) point. PCC is assumed as the connection point of distributed generation to the distribution system. The proposed method is implemented on a 15 bus grid in MATLAB/SIMULINK software. The results show the high accuracy of islanding detection of the proposed method. In this paper, one wind turbine is assumed as a distributed resource.


Keywords    Islanding Detection, Wavelet Transform, Feature Extraction, Wavenet



با توجه به افزایش روزافزون استفاده از منابع تولید پراکنده در شبکه‌های قدرت، می‌بایستی مشکلات مربوط به آن مورد توجه بیشتر قرار بگیرند. یکی از مشکلات اصلی جزیره‌ای شدن برنامه‌ریزی نشده است که برای سیستم قدرت و همچنین برای افرادی که با این سیستم کار می‌کنند، خطر ایجاد می‌کند و به همین خاطر مورد مطالعه‌ی بسیاری از محققین قرار گرفته است. در این مقاله یک روش محلی از نوع غیرفعال ارائه شده است. روش ارائه شده برپایه تبدیل موجک و کلاسه‌بندی جدیدی به نام شبکه عصبی موجکی (Wavenet) است. این روش بر روی یک شبکه‌ی 15 باسه در نرم‌افزار MATLAB/SIMULINK پیاده‌سازی شده است. نتایج بدست آمده نشان داده است که روش ارائه شده قادر است با دقت بسیار بالایی جزیره‌ای شدن منبع تولید پراکنده را تشخیص دهد. در این مقاله از توربین بادی به عنوان یک منبع تولید پراکنده استفاده شده است.


1. Kouhi, S., Ranjbar, M., Mohammadian, M. and Khavaninzadeh, M., "Economic aspect of fuel cell power as distributed generation",  International Journal of Engineering Transactions A: Basics, Vol. 27, No. 1 (2014) 57-62.
2. Ashtiani, N.A., Gholami, M. and Gharehpetian, G., "Optimal allocation of energy storage systems in connected microgrid to minimize the energy cost", in Electrical Power Distribution Networks (EPDC), 2014 19th Conference on, IEEE, (2014), 25-28.
3. Khamis, A., Shareef, H., Bizkevelci, E. and Khatib, T., "A review of islanding detection techniques for renewable distributed generation systems", Renewable and Sustainable Energy Reviews,  Vol. 28, (2013), 483-493.
4. Redfern, M., Usta, O. and Fielding, G., "Protection against loss of utility grid supply for a dispersed storage and generation unit", IEEE Transactions on Power Delivery,  Vol. 8, No. 3, (1993), 948-954.
5. Xu, W., Mauch, K. and Martel, S., "An assessment of dg islanding detection methods and issues for canada, report# cetc-varennes 2004-074 (tr), canmet energy technology centre–varennes", Natural Resources Canada,  (2004).
6. Karegar, H.K. and Sobhani, B., "Wavelet transform method for islanding detection of wind turbines", Renewable Energy,  Vol. 38, No. 1, (2012), 94-106.
7. Pham, J.-P., Denboer, N., Lidula, N., Perera, N. and Rajapakse, A., "Hardware implementation of an islanding detection approach based on current and voltage transients", in Electrical Power and Energy Conference (EPEC), IEEE. (2011), 152-157.
8. Hung, G.-K., Chang, C.-C. and Chen, C.-L., "Automatic phase-shift method for islanding detection of grid-connected photovoltaic inverters", IEEE Transactions on Energy Conversion,  Vol. 18, No. 1, (2003), 169-173.
9. Zeineldin, H. and Kennedy, S., "Sandia frequency-shift parameter selection to eliminate nondetection zones", IEEE Transactions on Power Delivery,  Vol. 24, No. 1, (2009), 486-487.
10. Zeineldin, H. and Conti, S., "Sandia frequency shift parameter selection for multi-inverter systems to eliminate non-detection zone", IET Renewable Power Generation,  Vol. 5, No. 2, (2011), 175-183.
11. Zeineldin, H.H. and Salama, M.M., "Impact of load frequency dependence on the ndz and performance of the sfs islanding detection method", IEEE Transactions on Industrial Electronics,  Vol. 58, No. 1, (2011), 139-146.
12. Lopes, L.A. and Sun, H., "Performance assessment of active frequency drifting islanding detection methods", IEEE Transactions on Energy Conversion,  Vol. 21, No. 1, (2006), 171-180.
13. Du, P., Ye, Z., Aponte, E.E., Nelson, J.K. and Fan, L., "Positive-feedback-based active anti-islanding schemes for inverter-based distributed generators: Basic principle, design guideline and performance analysis", IEEE Transactions on Power Electronics,  Vol. 25, No. 12, (2010), 2941-2948.
14. Yafaoui, A., Wu, B. and Kouro, S., "Improved active frequency drift anti-islanding detection method for grid connected photovoltaic systems", IEEE Transactions on Power Electronics,  Vol. 27, No. 5, (2012), 2367-2375.
15. Karimi, H., Yazdani, A. and Iravani, R., "Negative-sequence current injection for fast islanding detection of a distributed resource unit", IEEE Transactions on Power Electronics,  Vol. 23, No. 1, (2008), 298-307.
16. Ropp, M.E., Begovic, M., Rohatgi, A., Kern, G.A., Bonn, R. and Gonzalez, S., "Determining the relative effectiveness of islanding detection methods using phase criteria and nondetection zones", IEEE Transactions on Energy Conversion,  Vol. 15, No. 3, (2000), 290-296.
17. Funabashi, T., Koyanagi, K. and Yokoyama, R., "A review of islanding detection methods for distributed resources", in Power Tech Conference Proceedings, 2003 IEEE Bologna, IEEE. Vol. 2, (2003) 6. doi:    10.1109/PTC.2003.1304617
18. Jang, S.-I. and Kim, K.-H., "An islanding detection method for distributed generations using voltage unbalance and total harmonic distortion of current", IEEE Transactions on Power Delivery,  Vol. 19, No. 2, (2004), 745-752.
19. Freitas, W., Huang, Z. and Xu, W., "A practical method for assessing the effectiveness of vector surge relays for distributed generation applications", IEEE Transactions on Power Delivery,  Vol. 20, No. 1, (2005), 57-63.
20. Hagh, M.T. and Ghadimi, N., "Radial basis neural network based islanding detection in distributed generation", International Journal of Engineering, Transactions A: Basics,  Vol. 27, No. 7, (2013), 1061-1070.
21. Zeineldin, H. and Kirtley, J.L., "Performance of the OVP/UVP and OFP/UFP method with voltage and frequency dependent loads",  IEEE (2009). http://hdl.handle.net/1721.1/73162
22. Bae, B.-Y., Jeong, J.-K., Lee, J.-H. and Han, B.-M., "Islanding detection method for inverter-based distributed generation systems using a signal cross-correlation scheme", Journal of Power Electronics,  Vol. 10, No. 6, (2010), 762-768.
23. Bakhshi, M., Noroozian, R. and Gharehpetian, G., "Islanding detection scheme based on adaptive identifier signal estimation method", ISA Transactions,  Vol. 71, (2017), 328-340.
24. Vatani, M., Sanjari, M.J. and Gharehpetian, G.B., "Islanding detection in multiple‐dg microgrid by utility side current measurement", International Transactions on Electrical Energy Systems,  Vol. 25, No. 9, (2015), 1905-1922.
25. Bakhshi, M., Noroozian, R. and Gharehpetian, G.B., "Novel islanding detection method for multiple dgs based on forced helmholtz oscillator", IEEE Transactions on Smart Grid,  Vol. 9, No. 6, (2017), 6448 - 6460.
26. Ray, P.K., Mohanty, S.R. and Kishor, N., "Disturbance detection in grid-connected distributed generation system using wavelet and s-transform", Electric Power Systems Research,  Vol. 8, No. 3, (2011), 805-819.
27. Ezzt, M., Marei, M., Abdel-Rahman, M. and Mansour, M., "A hybrid strategy for distributed generators islanding detection", in IEEE PES Power Africa 2007 Conference and Exposition Johannesburg, South Africa, (2007).

Download PDF 

International Journal of Engineering
E-mail: office@ije.ir
Web Site: http://www.ije.ir