تعيين متغيرهاي كنترلي در سيستم قدرت به منظور بازيابي حداكثر بار
محورهای موضوعی : مهندسی برق و کامپیوترحسين افراخته 1 , محمودرضا حقی‌فام 2 , علی یزدیان ورجانی 3
1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
3 - دانشگاه تربیت مدرس
کلید واژه: الگوريتم ژنتيكبازيابي باربرنامه‌ريزي مجدد توليدتپ ترانسفورماتورقطع بار,
چکیده مقاله :
در اين مقاله يك روش جديد به منظور بازيابي حداكثر بار با تكيه بر مديريت برخي از متغيرهاي كنترلي در شرايط بروز عيب و قطعي‌هاي جزئي مانند قطع خط انتقال، خروج واحدهاي توليدي و غیره ارائه شده است. متغيرهاي كنترلي كه جهت حداكثرنمودن مقدار بار بازيابي‌شده به كار مي‌رود شامل تپ ترانسفورماتورهاي قدرت، برنامه‌ريزي مجدد واحدهاي توليد و در صورت نياز قطع بار خواهد بود. مدل‌سازي در سه مرحله انجام گرفته و اولويت بکارگيري متغيرهاي كنترلي در مراحل شبيه‌سازي متفاوت است. در مرحله اول از متغير كنترلي تپ ترانسفورماتورهاي قدرت، در مرحله دوم از مدل‌سازي هم‌زمان متغيرهاي كنترلي تپ ترانسفورماتورها و برنامه‌ريزي مجدد واحدهاي توليدي و در مرحله نهایي از بكارگيري هم‌زمان متغيرهاي تپ ترانسفورماتورهاي قدرت، برنامه‌ريزي مجدد واحدهاي توليدي و قطع بار استفاده شده است. با توجه به تعدد متغيرهاي كنترلي و غير خطي بودن فضاي پاسخ نهایي، بهينه‌سازي به كمك الگوريتم ژنتيك انجام شده و شبكه استاندارد IEEE-RTS با 24 شينه جهت بررسي قابليت‌هاي روش پيشنهادي و مطالعات عددي مورد استفاده قرار گرفته است.
This paper presents a new method to maximize load restoration in faulted condition in power systems. Control variables which are used to restore maximum load include tap of power transformers, generation rescheduling, and load shedding in the worst case. Modeling is done in three stages with various control variables arrangements. In the first stage of modeling, power transformer tap is used as a control variable. In the second stage, power transformers taps and generations rescheduling are considered. In the last stage, load shedding as another variable is added to decision variable spaces. Since the number of variables is high and final solution space can be nonlinear, genetic algorithm is used in the optimization process. The capabilities of the proposed method were assessed using IEEE-RTS test system with satisfactory results.
[1] M. M. Adibi and et al., "Power system restoration - a task force report," IEEE Trans. on Power Systems, vol. 2, no. 2, pp. 271-277, May 1987.
[2] R. Nadira, T. E. Dy Liacco, and K. A. Loparo, "A hierarchical interactive approach to electric power system restoration," IEEE Trans. on Power Systems, vol. 7, no. 3, pp. 1123-1131, Aug. 1992.
[3] D. N. Ewart, "Whys and wherefores of power system blackouts," IEEE Spectrum Mag., pp. 36-41, Apr. 1978.
[4] M. M. Adibi, Power System Restoration Methodologies & Implementation Strategies, Wiley-IEEE Press, 2000.
[5] F. F. Wu and A. Monticelli, "Analytical tools for power system restoration - conceptual design," IEEE Trans. on Power Systems, vol. 3, no. 1, pp. 10-16, Feb. 1988.
[6] P. Gomes, A. C. S. de Lima, and A. de Padua Guarini, "Guidelines for power system restoration in the Brazilian system," IEEE Trans. On Power Systems, vol. 19, no. 2, pp. 1159 - 1164, May. 2002.
[7] O. Y. Bong. M. R. Lee, and N. H. Lee, "Development of automatic power restoration systems in KEPCO real power system," in Proc. Pacific. IEEE/PES Trans. and Distribution Conf. and Exhibition, vol. 3, pp. 1691-1694, Oct. 2002.
[8] M. Sforna and V. C. Bertanza, "Restoration testing and training in italian ISO," IEEE Trans. on Power Systems, vol. 17, no. 4, pp. 1258-1264, Nov. 2002.
[9] R. Kearsley, "Restoration in sweden and experience from the blackout of 1983," IEEE Trans. on Power Systems, vol. 2, no. 2, pp. 422-428, May 1987.
[10] L. H. Fink, K. -L. Liou, and C. -C. Liu, "From generic restoration actions to specific restoration strategies," IEEE Trans. on Power Systems, vol. 10, no. 2, pp. 745-751, May 1995.
[11] Y. -T. Hsiao and C. -Y. Chien, "Enhancement of restoration service in distribution systems using a combination fuzzy - GA method," IEEE Trans. on Power Systems, vol. 15, no. 4, pp. 1394-1400, Nov. 2000.
[12] T. Nagata, H. Sasaki, and R. Yokoyama, "Power system restoration by joint usage of expert system and mathematical programming approach," IEEE Trans. on Power Systems, vol. 10, no. 3, pp. 1473-1479, Aug. 1995.
[13] S. Lee, S. Lim, and B. Ahn, "Service restoration of primary distribution systems based on fuzzy evaluation of multi - criteria," IEEE Trans. on Power Systems, vol. 13, no. 3, pp. 1156-1163, Aug. 1998.
[14] R. J. Kafka, D. R. Penders, S. H. Bouchey, and M. M. Adibi, "System restoration plan development for a metropolitan electric system," IEEE Trans. on Power Appar. and Systems, vol. 100, no. 8, pp. 3703-3713, Aug. 1981.
[15] T. Sakaguchi and K. Matsumoto, "Development of a knowledge based system for power system restoration," IEEE Trans. on Power Appar. and Systems, vol. 102, no. 2, pp. 320-329, Feb. 1983.
[16] D. S. Kirschen and T. L. Volkmann, "Guiding a power system restoration with an expert system," IEEE Trans. on Power Systems, vol. 6, no. 2, pp. 556-566, May 1991.
[17] M. M. Adibi, "New approach in power system restoration," IEEE Trans. on Power Systems, vol. 5, no. 4, pp. 1428-1434, Nov. 1992.
[18] I. Helal, H. Fathalla, M. M. S. Mansour, and S. Al - Debieky, "Power system restoration using expert system technique," in Proc. Int. Conf. on Electrical, Electronic and Computer Engineering, pp. 747-752, Sep. 2004.
[19] M. -Y. Chow, L. S. Taylor, and M. -S. Chow, "Time of outage restoration analysis in distribution systems," IEEE Trans. on Power Delivery, vol. 11, no. 3, pp. 1652-1658, Jul. 1996.
[20] M. M. Adibi and D. P. Milanicz, "Estimating restoration duration," IEEE Trans. on Power Systems, vol. 14, no. 4, pp. 1493-1498, Nov. 1999.
[21] I. Watanabe and M. Nodu, "A genetic algorithm for optimizing switching sequence of service restoration in distribution systems," in Proc. Congress on Evolutionary Computation, vol. 2, pp. 1683-1690, Jun. 2004.
[22] N. G. Bretas, A. C. B. Delbem, and A. de Carvalho, "Optimal energy restoration for general distribution systems by genetic algorithms," in Proc. of Power System Technology Int. Conf., POWERCON '98, vol. 1, pp. 43-47, Aug. 1998.
[23] S. Toune, H. Fudo, T. Genji, and Y. Fukuyama, "Comparative study of modern heuristic algorithms to service restoration in distribution systems," IEEE Trans. on Power Delivery, vol. 17, no. 1, pp. 173-181, Jan. 2002.
[24] A. Ketabi, A. M. Ranjbar, and R. Feuillet, "A new method for dynamic calculation of load steps during power system restoration," in Canadian Conf. on Electrical and Computer Engineering, vol. 1, pp. 158-162, Mar. 2000.
[25] T. S. Sidhu, et al., "Protection issues during system restoration," IEEE Trans. on Power Delivery, vol. 20, no. 1, pp. 47-56, Jan. 2005.
[26] IEEE RTS Task Force of APM Subcommittee, "The reliability test system-1996," IEEE Trans. on Power Systems, vol. 14, no. 3, pp. 1010-1020, Aug. 1999.
[27] D. Goldberg and E. David, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison - Wesly, 1989.
[28] A. S. Chung and F. Wu, "An extensible genetic algorithm framework for problem solving in a common environment," IEEE Trans. on Power Systems, vol. 15, no. 1, pp. 15-21, Feb. 2000.
