تشخیص جزیره‌های الکتریکی در شبکه‌های توزیع دارای تولیدات پراکنده با استفاده از تبدیل موجک گسسته و شبکه عصبی مصنوعی
محورهای موضوعی : مهندسی برق و کامپیوترمهرداد حیدری ارجلو 1 * , سیدقدرت‌اله سیف‌السادات 2 , مرتضی رزاز 3
1 - دانشگاه شهید چمران اهواز
2 - دانشگاه شهید چمران اهواز
3 - دانشگاه شهید چمران اهواز
کلید واژه: تبدیل موجک گسسته تولیدات پراکنده جزیره الکتریکی و شبکه عصبی مصنوعی,
چکیده مقاله :
در این مقاله برای تشخیص جزیره‌های الکتریکی، یک الگوریتم جدید مبتنی بر تحلیل سیگنال‌های حالت گذرا با استفاده از تبدیل موجک گسسته (DWT) و شبکه عصبی مصنوعی (ANN) ارائه می‌گردد. شبکه عصبی برای دسته‌بندی حوادث به حالت‌های "جزیره" یا "غیر جزیره" آموزش داده می‌شود. ویژگی‌های مورد نیاز دسته‌بندی، از طریق تبدیل موجک گسسته سیگنال‌های گذرای ولتاژ و جریان DGها استخراج می‌شوند. برای شبیه‌سازی الگوریتم از نرم‌افزارهای DIGSILENT، MATLAB و WEKA استفاده شده است. روش پیشنهادی روی یک سیستم توزیع ولتاژ متوسط CIGRE با دو نوع DG مختلف آزمایش می‌شود. این مقاله، الگوریتم رله نهایی را با تحلیل انجام‌گرفته از میان 162 طرح انتخاب می‌کند تا رله انتخابی از نظر شاخص‌های مختلف از جمله دقت، سرعت، سادگی و هزینه، بهترین کارایی را داشته باشد. با تحلیل و بررسی‌های صورت‌گرفته در رله انتخابی DGها، از سیگنال ولتاژ، موجک مادر 4db و سطح هفتم تبدیل موجک استفاده می‌شود. نتایج شبیه‌سازی نشان می‌دهد که این روش می‌تواند جزیره‌های الکتریکی را در مقایسه با روش‌های موجود در زمان کوتاه‌تر و با دقت بالاتری تشخیص دهد.
In this paper a new algorithm is provided for detecting of electrical islands, based on analysis of transient signals using discrete wavelet transform (DWT) and artificial neural network (ANN). The neural network is taught for Classification of events to the "islands" or "non-islands". Needed features for classification are extracted by DWT of DG transient voltage signal. DIgSILENT, MATLAB and WEKA softwares are used for simulation. Proposed method is tested on a CIGRE medium voltage distribution system with two different types of DGs. The final method is chosen from among 162 relay projects with respect to different criteria, including accuracy, speed, simplicity and cost efficiency is the best. With The analysis done in the best relay selection for DGs, the voltage signal, the mother wavelet db4 and seventh level wavelet transform are used. Simulation results show that this method in compared with existing methods, can detect the electrical islands, with a shorter time and higher accuracy.
[1] A. M. Massoud, K. H. Ahmed, S. J. Finney, and B. W. Williams, "Harmonic distortion-based island detection technique for inverter-based distributed generation," IET Renew. Power Gener., vol. 3, no. 4, pp. 493-507, Dec. 2009.
[2] G. Hernandez-Gonzalez and R. Iravani, "Current injection for active islanding detection of electronically-interfaced distributed resources," IEEE Trans. Power Deliv., vol. 21, no. 3, pp. 1698-1705, Jul. 2006.
[3] A. Pigazo, M. Liserre, R. A. Mastromauro, V. M. Moreno, and A. Dell'Aquila, "Wavelet-based islanding detection in grid-connected PV systems," IEEE Trans. Industrial Electronics, vol. 56, no. 11, pp. 4445-4455, Nov. 2009.
[4] IEEE Standard 1547.2-2008: IEEE Application Guide for IEEE Std. 1547™, IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems.
[5] H. H. Zeineldin and J. L. Kirtley, "A simple technique for islanding detection with negligible nondetection zone," IEEE Trans. Power Delivery, vol. 24, no. 2, pp. 779-786, Apr. 2009.
[6] S. P. Chowdhurya, S. Chowdhurya, and P. A. Crossleyb, "Islanding protection of active distribution networks with renewable distributed generators: a comprehensive survey," Electric Power Systems Research, vol. 79, no. 6, pp. 984-992, Jun. 2009.
[7] Y. H. Liy, T. S. Luor, S. J. Huang, and J. M. Lin, Method and System for Detecting Stand-alone Operation of a Distributed Generating System, U.S. Patent 7 342 758, 2008.
[8] C. T. Hsieh, J. M. Lin, and S. J. Huang, "Enhancement of islanding-detection of distributed generation systems via wavelet transform-based approaches," Int. J. Elect. Power Energy Syst., vol. 30, no. 1, pp. 575-580, Nov. 2008.
[9] A. Pigazo, V. M. Moreno, M. Liserre, and A. Dell'Aquila, "Wavelet based islanding detection algorithm for single-phase PV distributed generation systems," in Proc. IEEE Int. Symp. Industrial Electronics, vol. 1, pp. 2409-2413, Vigo, Spain, 4-7 Jun. 2007.
[10] X. Wilsun, K. Mauch, and S. Martel, "An assessment of distributed generation islanding detection methods and issues for Canada," Natural Resources Canada, 2004.
[11] O. Samuelsson and N. Strath, "Islanding detection and connection requirements," in Proc. IEEE Power Engineering Society General Meeting, vol. 1, 6 pp., Jun. 2007.
[12] D. Persson, Islanding Detection in Power Electronic Converter Based Distributed Generation, Master Thesis, Industrial Electrical Engineering and Automation, 2007.
[13] M. S. El-Nozahy, E. F. El-Saadany, and M. M. A. Salama, "A robust wavelet-ANN based technique for islanding detection," in Proc. IEEE Power and Energy Society General Meeting, 8 pp., Jul. 2011.
[14] Y. Fayyad and A. Osman, "Neuro-wavelet based islanding detection technique," in Proc. IEEE Electrical Power & Energy Conf., 6 pp., 25-27 Aug. 2010.
[15] N. W. A. Lidula and A. D. Rajapakse, "A pattern recognition approach for detecting power islands using transient signals-part I: design and implementation," IEEE Trans. on Power Delivery, vol. 25, no. 4, pp. 3070-3077, Oct. 2010.
[16] K. El-Arroudi, G. Joos, I. Kamwa, and D. T. McGillis, "Intelligent based approach to islanding detection in distributed generation," IEEE Trans. Power Del., vol. 22, no. 2, pp. 828-835, Apr. 2007.
[17] L. Safavian, W. Kinsner, and H. Turanli, "A probabilistic approach to classification of transients in power systems," in Proc. IEEE 2006 Canadian Conf. on Electrical and Computer Engineering, CCECE06, vol. 1, pp. 1342-1346, May 2006.
[18] R. Kunte, A Wavelet Transform-Based Islanding Detection Algorithm for Inverter Assisted Distributed Generators, Ms.C. Thesis, Tennessee Technological University, 2009.
[19] N. W. A. Lidula and N. Perera, "Investigation of a fast islanding detection methodology using transient signals," in Proc. Power and Energy Society General Meeting, 6 pp., 26-30 Jul. 2009.
[20] A. Graps, "An introduction to wavelets," Comput. Sci. Eng., vol. 2, no. 2, pp. 50-61, Summer 1995.
[21] C. H. Kim and R. Agganrval, "Wavelet transforms in power systems-part 1: general introduction to the wavelet transforms," IEEE Power Eng. J., vol. 14, no. 2, pp. 81-87, Apr. 2000.
[22] C. H. Kim and R. Agganrval, "Wavelet transforms in power systems-part 2: examples of application to actual power system transients," IEEE Power Eng. J., vol. 15, no. 4, pp. 193-202, Aug. 2000.
[23] R. Beale and T. Jackson, Neural Network: an Introduction, Institute of Physics Publishing, 1998.
[24] I. Daubechies, Ten Lectures on Wavelets, Montpelier, VT: Capital City Press, 1992.
[25] H. A. Darwish, M. H. Farouk, A. M. I. Taalab, and N. M. Mansour, "Investigation of real-time implementation of DSP-based DWT for power system protection," in Proc. IEEE PES Transmission and Distribution Conference and Exhibition, vol. 1, pp. 1258-1263, 21-24 May 2006.
[26] N. Perera and A. D. Rajapakse, Rapid Isolation of Faults in Power Networks with Distributed Generators, M.Sc. Dissertation, Univ. Manitoba, Winnipeg, MB, Canada, May 2007.
[27] Y. Fayyad and A. Osman, "Neuro-wavelet based islanding detection technique," in Proc. 2010 IEEE Electrical Power & Energy Conf., 6 pp., 25-27 Aug. 2010
[28] E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The WEKA data mining software: an update," Mark Hall, SIGKDD Explorations, vol. 11, no. 1, pp. 10-18, Jun. 2009.
[29] K. Rudion, A. Orths, Z. A. Styczynski, and K. Strunz, "Design of benchmark of medium voltage distribution network for investigation of DG integration," in Proc. IEEE PES Conf., 6 pp., Montreal, Canada, Jun. 2006.
[30] N. W. A. Lidula and A. D. Rajapakse, "A pattern-recognition approach for detecting power islands using transient signals-part II: performance evaluation," IEEE Trans. on Power Delivery, vol. 27, no. 3, pp. 1071-1080, Jul. 2012.