طراحی پایدارساز فازی در سیستم‏های قدرت چند ماشینه با استفاده از الگوریتم جستجوی هارمونی

نویسندگان

دانشگاه سمنان

چکیده

در این مقاله طراحی و بهینه‌سازی قوانین کنترل‌کننده فازی در سیستم قدرت چند ماشینه با استفاده از الگوریتم جستجوی هارمونی ارائه شده است. استفاده از کنترل‌کننده فازی PID یکی از روش‌های مناسب برای پایداری در سیستم-های غیرخطی می‌باشد. رفتار کنترل‌کننده‌های فازی به اطلاعات طراحی شامل انتخاب توابع عضویت و قوانین کنترلی بستگی دارند. در روش‌های طراحی سنتی، اطلاعات طراحی مبتنی بر تجربه افراد خبره است که از طریق آزمون سعی و خطا تعیین می‌گردد. بنابراین طراحی یک کنترل‌کننده مناسب زمان‌بر می‌باشد. بنابراین انتخاب بهینه قوانین فازی و یا شکل توابع عضویت مسأله بسیار مهمی می‌باشد. و این مساله بدون نیاز به تجربیات افراد خبره از اهمیت ویژه‌ای برخورداراست. از طرفی الگوریتم پیشنهادی هارمونی نیز در بررسی نتیجه عملکرد اجزا به دنبال هماهنگی مطلوب می‌باشد که در حل مسائل بهینه‌سازی به دنبال یافتن بهترین مسیر است تا بوسیله آن هزینه توابع محاسباتی را کاهش دهد. لذا کنترل‌کننده پیشنهادی در نقاط کار مختلف بر روی سیستم قدرت استاندارد سه ماشینه IEEE و ده ماشینه New-England مورد آزمایش قرار گرفته و نتایج تحلیل مقادیر ویژه سیستم و شبیه‌سازی با دیگر روش‌ها مقایسه گردیده است.

کلیدواژه‌ها

عنوان مقاله [English]

OPTIMAL DESIGN OF FUZZY POWER SYSTEM STABILIZER IN MULTI-MACHINE ENVIRONMENT BY HARMONY SEARCH ALGORITHM

نویسندگان [English]

  • O. Abedinia
  • N. Amjady
semnan
چکیده [English]

This paper presents an optimal design of Fuzzy Power System Stabilizer (FPSS) using Harmony Search Algorithm (HSA) in multi-machine power system. The PID controller is one of the appropriate techniques to damp low frequency oscillation in nonlinear systems. The proposed controller is based on their rule base and membership function information. In conventional techniques the information is obtained by trial and error which needs too much time. So, finding the optimum value of rule base or membership function is really important. Accordingly, HAS is proposed in this paper to find the optimum value of rule base by considering the power system constrains and factors. This newly developed control strategy mixed the advantage of HSA and Fuzzy controller with simple structure while is easy to implement. Hence, the proposed controller is tested over the New England 10-unit 39-bus standard power system and 9 buses IEEE power system, under various system configurations and loading conditions, to illustrate the performance of the proposed method. The effectiveness of proposed controller is compared with other techniques. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed controller.

کلیدواژه‌ها [English]

  • Power system stabilizer
  • Fuzzy Controller
  • Rule Base
  • Multi-machine system
  • Harmony Search Algorithm

مراجع

 
[1]    Basler, M. J., Schaefer, R. C., (2008), "Understanding Power System Stability", IEEE Trans. Industry Applications, 2008, Vol. 44, pp. 463-474.
[2]    Abe, S. and Doi, A., (1983), "A New Power System Stabilizer Synthesis in Multimachine Power Systems," IEEE Trans. PAS, Vol. 102, No. 12, pp. 3910-3918.
[3]    Yu, Y. N. and Li, Q., (1990), "Pole-Placement Power System Stabilizers Design of an Unstable Nine-Machine System," IEEE Trans. PWRS, Vol. 5, No. 2, pp. 353-358.
[4]    Padiyar, K. R., (2006), " Power System Dynamics, Stability and Control", Second Ed..
[5]    Kundur, P., (1994), “Power System Stability and Control”, McGraw-Hill Inc., New York.
[6]    El-Zonkoly, A. M., Khalil, A. A. and Ahmied, N. M., (2008), “Optimal Tuning of Lead-Lag and Fuzzy Logic Power System Stabilizers Using Particle Swarm Optimization", Expert System with Applications, Vol. 10, pp. 1-10.
[7]    Abedinia, O., Amjady, N., Izadfar, H.R., Shayanfar, H.A., (2012), “Multi-machine Power System Oscillation Damping: Placement and Tuning PSS VIA Multi-objective HBMO”, “Technical and Physical Problems of Engineering” (IJTPE), Issue. 12, Vol. 4, No. 3, pp:1-8.
[8]    Abedinia , O., Jalili, A., (2011), “Optimal Rule-Base in Multi-Machine Fuzzy PSS Using Genetic Algorithm”, Australian Journal of Basic and Applied Sciences, Vol. 5, No. 10, pp: 1424-1434.
[9]    James, M. A., (2001), "Multi-stage fuzzy PID controller with fuzzy switch". In: Proceeding of the IEEE international conference on control application, vol. 4, p: 323–27.
[10]                         Hwang, J. H., Kim, D. W., Lee, J. H. and An, Y. J., (2008), “Design of Fuzzy Power System Using Adaptive Evolutionary Algorithm”, Engineering Applications of Artificial Intelligence, vol. 21, pp. 86-96.
[11]                         Abdel-Magid, Y. L., Abido, M. A., (2003), ”Optimal Multi-objective Design of  Robust Power System Stabilizers Using Genetic Algorithms”, IEEE  Transaction on Power Systems, Vol. 18, No.  9. PP. 256-267.
[12]                         Glover, F., (1990), “Artificial Intelligence Heuristic Frameworks and Tabu Search”, Managerial and Decision Economics, Vol. 11, No 2. PP. 365-375.
[13]                         Chhavali, S., Pahwa, A. and Das, S.. (2002),  ”A Genetic Algorithm Approach for Optimal Distribution Feeder Restoration Duting Cold Load Pickup” , In proc. Of the 2002 congress on evolutionary computation, Vol. 5, No. 4, PP. 1816-1819.
[14]                         Segal, R., Sharma, A., Kothari, M. L., (2004), "A Self-tuning Power System Stabilizer Based on Artificial Neural Network", Vol. 26, pp. 423-430.
[15]                         Vasebi, A., Fesanghary, M., Bathaee, SMT., (2007), “Combined heat and power economic dispatch by harmony search algorithm”, Electrical Power Energy Syst Vol. 29, no. 10, pp. 713–719.
[16]                         Hyun Hwang, G., Xan Kim, D., Hyne. Lee, J. and Joo, Y. An, (2008), “Design of Fuzzy Power System Stabilizer Using Adaptive Evolutionary Algorithm”, Engineering Applications of Artificial Intelligence, Vol. 21, No. 6, PP. 86-96.
[17]                         Kazimi, A., Sohrforouzani, M. V., (2006), “Power System Damping Using Fuzzy Controlled Facts Devices”,  Electrical Power and Energy Systems, Vol. 28, No. 2, PP. 349-357.
[18]                         Tang, K. S., Man, K. F., Chen, G., Kwong, S., (2001), “A GA-optimized Fuzzy PID Controller For Nonlinear Systems”, The 27th Annual Conference of IEEE Industrial Electronics Socity, Vol, 20. No. 5,  PP. 718-723.
[19]                         Cheong, F., Lai, R., (2000), “Constraining the Optimization of a Fuzzy Logic Controller Using an Enhanced Genetic Algorithm”, IEEE Transactions on Systems, MAN, and Cybernetics, Vol. 30, No. 1.
[20]                         Juang, C. F., Lu, C. F., (2002), “Power System Load Frequency Control with Fuzzy Gain Scheduling Designed by New Genetic Algorithms”, IEEE International Conference on Plasma Science, Vol. 1, No. 7 , PP.64-68.
[21]                         Geem, ZW., Tseng, C., Park, Y., (2005), “Harmony search for generalized orienteering problem”, best touring in China. Springer Lect Notes Comput Sci, pp. 741–7150.
[22]                         Abedinia, O., Barazande, Ebrahim S., Amjady, N., (2012), “Solving Optimal Unit Commitment Problem Based on Wind Power Effects Using Harmony Search Algorithm”, International Journal of Basic and Applied Science (IJBAS), Vol. 2, No. 11, pp: 11764-11773.
[23]                         Geem, ZW., Kim, JH., Loganathan, GV., (2002),  “Harmony search optimization: application to pipe network design,  Int J Model Simulat., vol. 22, no. 2, pp. 125–133.
[24]                         Maslennikov, V. A. and Ustinov, S. M., (1996), "The Optimization Method for Coordinated Tuning of Power System Regulators," Proc. 12th Power System Computation Conference PSCC, Dresden,, pp. 70-75.
[25]                         Abdel-Magid, Y. L., Abido, M. A., Al-Baiyat, S., and Mantawy, A. H., (1999), "Simultaneous Stabilization of Multimachine Power Systems via Genetic Algorithms," IEEE Trans. PWRS, Vol. 14, No. 4, pp. 1428-1439.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
مدل سازی در مهندسی
دوره 12، شماره 36
خرداد 1393
صفحه 1-15

فایل ها

سابقه مقاله

  • تاریخ دریافت: 09 بهمن 1395
  • تاریخ بازنگری: 02 مهر 1396
  • تاریخ پذیرش: 09 بهمن 1395

هم رسانی

ارجاع به این مقاله

آمار