Optimal Reactive Power Dispatch using Improved Differential Evolution Algorithm

Majlesi Journal of Electrical Engineering

مقاله 10، دوره 8، شماره 1، خرداد 2014، صفحه 69-78   

نوع مقاله: Review Article

نویسندگان

Hamid Falaghi؛ Arsalan Najafi^*

Department of Electrical Engineering, University of Birjand, Birjand, Iran

چکیده

Reactive power dispatch plays a key role in secure and economic operation of power systems. Optimal reactive power dispatch (ORPD) is a non-linear optimization problem which includes both continues and discrete variables. Due to complex characteristics, heuristic and evolutionary based optimization approaches have became effective tools to solve the ORPD problem. In this paper a new optimization approach based on improved differential evolution (IDE) has been proposed to solve the ORPD problem. IDE is an improved version of differential evolution optimization algorithm in which new solutions are produced in respect to global best solution. In the proposed approach, IDE determines the optimal combination of control variables including generator voltages, transformer taps and setting of VAR compensation devices to obtain minimum real power losses. In order to demonstrate the applicability and efficiency of the proposed IDE based approach, it has been tested on the IEEE 14 and 57-bus test systems and obtained results are compared with those obtained using other existing methods. Simulation results show that the proposed approach is superior to the other existing methods.الأمثل قوة رد الفعل DISPATCH عن طریق تحسن التفاضلیة تطور الخوارزمیةرد الفعل ارسال قوة یلعب دورا رئیسیا فی عملیة آمنة والاقتصادیة لأنظمة الطاقة. الأمثل على رد الفعل ارسال قوة (ORPD) هو الحل الأمثل لغیر الخطی الذی یشمل کلا من تواصل والمتغیرات المنفصلة. نظرا لخصائص معقدة، وأصبح النهج الأمثل الکشف عن مجریات الأمور والتطور على أساس أدوات فعالة لحل مشکلة ORPD. فی هذه الورقة تم اقتراح نهج التحسین جدید یقوم على تحسین تطور التفاضلیة (IDE) على حل مشکلة ORPD. IDE هو نسخة محسنة من التفاضلیة خوارزمیة التطور الأمثل الذی یتم إنتاج حلول جدیدة فیما یتعلق أفضل حل عالمی. فی النهج المقترح، یحدد IDE الجمع الأمثل للمتغیرات بما فی ذلک مراقبة الفولتیة مولد والصنابیر المحولات ووضع أجهزة تعویض VAR للحصول على الحد الأدنى من الخسائر السلطة الحقیقیة. من أجل إثبات إمکانیة تطبیق وکفاءة نهج IDE على أساس المقترح، وقد تم اختباره على أنظمة اختبار IEEE 14 و 57 باص وحصل تتم مقارنة النتائج مع تلک التی تم الحصول علیها باستخدام طرق أخرى موجودة. وتبین نتائج المحاکاة أن النهج المقترح متفوقة على الطرق الأخرى القائمة. 

کلیدواژه‌ها

Improved Differential Evolution؛ en؛ Loss Minimization؛ Optimal Reactive Power Dispatch؛ Power System Operation

مراجع

[1] P. Subbaraj and PN. Rajnarayananb, “Optimal reactive power dispatch using self-adaptive real coded genetic algorithm,” Electr. Power Syst. Res., Vol. 79, pp. 374–381, 2009.

[2] J. A. Momoh, M. E. El-Hawary and R. Adapa, “A review of selected optimal power flow literature to 1993 part I & II,” IEEE Trans. Power Syst., Vol. 14, pp. 96–111, 1999.

[3] D. I. Sun, B. Ashley, B. Brewar and A. Hughes, “Optimal power flow by Newton approach,” IEEE Trans. Power Apparsyst, Vol. 103, pp. 2864–2880, 1984.

[4] F. C. Lu, Y. Y. Hsu, “Reactive power/voltage control in a distribution substation using dynamic programming,” IEE Proc. Gen Transm. Distrib., Vol. 142, pp. 639–645, 1995.

[5] K. Y. Lee, Y. M. Park and J. L. Ortiz, “A united approach to optimal real and reactive power dispatch,” IEEE Trans. Power Syst., Vol. 1, pp. 1147–1153, 1985.

[6] Y. Y. Hong, D. I. Sun, S. Y. Lin and C. J. Lin, “Multi-year multi-case optimal AVR planning,” IEEE Trans. Power Syst., Vol. 5, pp. 1294–1301, 1990.

[7] N. Deeb and S. M. Shahidepour, “Linear reactive power optimization in a large power network using the decomposition approach,” IEEE Trans. Power Syst., Vol. 5, pp. 428–435, 1990.

[8] K. Aoki, M. Fan and A. Nishikori, “Optimal var planning by approximation method for recursive mixed integer linear programming,” IEEE Trans. Power Syst., Vol. 3, pp. 1741–1747, 1998.

[9] A. G. Bakirtzis and A. Meliopous, “Incorporation of switching operations in power system corrective control computation,” IEEE Trans. Power Syst., Vol. 2, pp. 669–676, 1987.

[10] G. Bakare, G. Venayagamoorthy and U. Aliyu, “Reactive power and voltage control of the Nigerian grid system using microgenetic algorithm,” IEEE Power Eng. Soc General Meeting, San Francisco, CA, Vol. 2, pp. 1916–1922, 2005.

[11] M. Abido, “Optimal power flow using particle swarm optimization,” J. Electr. Power Energy Syst., Vol. 24, pp. 563–571, 2002.

[12] H. Yoshida, Y. Fukuyama, K. Kawata, S. Takayama, Y. Nakanishi, “A particle swarm optimization for reactive power and voltage control considering voltage security assessment,” IEEE Trans. Power Syst. Vol. 15, pp. 1232–1239, 2001.

[13] Q. Wu and J. Ma, “Power systems optimal reactive power dispatch using evolutionary programming,” IEEE Trans. Power Syst., Vol. 10, pp. 1243–1249, 1995.

[14] C. H. Liang, C. Y. Chung, K. P. Wong, X. Z. Duan and C. T. Tse, “Study of differential evolution for optimal reactive power flow,” IET Gen. Transm. Disrib, Vol. 1, pp. 253–260, 2007.

[15] M. Varadarajan, K. S. Swarup, “Differential evolutionary algorithm for optimal reactive power dispatch,” Electr. Power Energy Syst., Vol. 30, pp. 435–441, 2008.

[16] A. Abou, E. Ela, M. Abido and S. R. Spea, “Differential evolution algorithm for optimal reactive power dispatch,” Electr. Power Syst. Res., Vol. 81, pp. 458-64, 2011.

[17] A. Khazali and M. Kalantar, “Optimal reactive power dispatch based on harmony search algorithm,” Elect. Power Energy Syst., Vol. 33, pp. 684–692, 2011.

[18] J. Vlachogiannis and J. Ostergaard, “Reactive power and voltage control based on general quantum genetic algorithms,” Expert Syst. Appl., Vol. 36, pp. 6118–6126, 2009.

[19] Y. Hsiao, C. Liu, H. Chiang and Y. Chen, “A new approach for optimal VAR sources planning in large scale electric power systems,” IEEE Trans. Power Syst., Vol. 8, pp. 988–996, 1993.

[20] C. Dai, W. Chen, Y. Zhu and X. Zhang, “Seeker Optimization Algorithm for Optimal Reactive Power Dispatch,” IEEE Trans. Power Syst., Vol. 24, pp. 1218-1231, 2009.

[21] A. Esmin, G. Lambert-Torres and A. Zambroni de Souza, “A hybrid particle swarm optimization applied to loss power minimization,” IEEE Trans. Power Syst., Vol. 20, pp. 859–866, 2005.

[22] T. Niknam, M. R. Narimani, M. Jabbari and Malekpour, “A modified shuffle frog leaping algorithm for multi-objective optimal power flow,” Energy, Vol. 36, pp. 6420-6432, 2011.

[23] A. Saraswat and A. Saini, “Multi-objective optimal reactive power dispatch considering voltage stability in power systems using HFMOEA,” Engineering Applications of Artificial Intelligence, Vol. 26, pp. 390-404, 2013.

[24] A. Rabiee, M. Vanouni and M. Parniani, “Optimal reactive power dispatch for improving voltage stability margin using a local voltage stability index,” Energy Conversion and Management, Vol. 59, pp. 66-73, 2012.

[25] W. Lebow, R. Rouhani, R. Nadira, P. B. Ushoroand R. K. Mishra, D. W. Sobieski, M. K. Pal and P. Bhavaraju, “A hierarchical approach to VAR optimization in system planning,” IEEE Trans. Power App., Vol. 104, pp. 2051–2057, 1985.

[26] R. Storn and K. Price, “Differential evolution – A simple and efficient adaptive scheme for global optimization over continuous spaces,” Int. Comput. Sci. Inst., Berkeley, CA, 1995.

[27] D. Zaharie, “Influence of crossover on the behavior of differential evolution algorithms,” Appl. Soft Comput.; Vol. 9, pp.1126–1138, 2009.

[28] K. Papadogiannis, N. Hatziargyriou and J. T. Saraiva, “Bid based coupled active/reactive dispatch using simulated annealing,” Eng. Intel. Syst., Vol. 12, pp. 175–184, 2003.

[29] System data (2006, December). Available from: .