کاهش نوسانات زیر سنکرون با استفاده از ادوات D-FACTS با کنترل‌کننده‌های هوشمند

نوع مقاله: مقاله پژوهشی

نویسندگان

گروه مهندسی برق ، دانشکده فنی و مهندسی، دانشگاه شهرکرد، شهرکرد، چهارمحال و بختیاری، ایران

چکیده

هنگامی که یک توربین-ژنراتور به یک خط انتقال طولانی وصل می‌شود ممکن است عوارض جانبی مانند پدیده   SSR در آن به وجود آید. هدف این است که با استفاده از قابلیت‌های جبران کننده سری (DSSC) به عنوان یک عضو از خانواده  D- FACTS به کاهش  SSR پرداخته شود. برای رسیدن به هدف مورد نظر از کنترل‌کننده فازی، بهینه سازی ازدحام ذرات (PSO) و شبکه عصبی استفاده شده است. بهینه سازی ازدحام ذرات (PSO) بر اساس کنترل‌کننده میرایی مرسوم (CDC)، منطق فازی بر اساس کنترل  میرایی (FLBDC) و شبکه عصبی نیز بر اساس کنترل میرایی با استفاده از آموزش داده‌های سرعت و تغییرات سرعت طراحی شده اند. پایداری سیستم از طریق شبیه‌سازی در حوزه زمان و با مطالعه شاخص عملکرد (PI) بر اساس دینامیک سیستم قدرت مورد بررسی قرار گرفته است. نتایج شبیه‌سازی با استفاده از نرم افزار Matlab /    Simulinkآورده شده است. موارد مورد مطالعه به منظور نشان دادن این واقعیت است که الگوریتم های مربوطه  قادر به کاهش تشدیدهای زیر سنکرون می‌باشند. نشان داده شده که کنترل‌‌کننده فازی و الگوریتم بهینه‌سازی  PSOبه همراه شبکه عصبی به خوبی می‌توانند این نوسانات ‌را کاهش دهند.

کلیدواژه‌ها


عنوان مقاله [English]

Reduction of Sub-synchronous Resonances with D-FACTS Devices using intelligent Control ,

نویسندگان [English]

  • Zahra Amini
  • Abbas Kargar
Department of Electrical Engineering, Shahrekord University, Shahrekord, Iran
چکیده [English]

When a turbine–generator set connect to a long transmission line, may results side effects such as Sub-Synchronous Resonances (SSR). The capabilities of the Distributed Static Series Compensator (DSSC) as a member of the family of D-FACTS can be used to reduce these SSR. To achieve this desired goal, the fuzzy controller, Particle Swarm Optimization (PSO) and artificial neural network is used to control of the DSSC. Particle swarm optimization is designed Based on the Conventional Damping Controller (CDC) and fuzzy logic is designed based on damping controller (FLBDC) and damping control based on artificial neural network trained using the fast pace of changes has been designed. Stability of the system is analysed by simulations in the time domain with performance index (PI). All simulations are done using Matlab / Simulink software. Case studies show that proposed algorithms can reduce SSR in the system.All simulations are done using Matlab / Simulink software. Case studies show that proposed algorithms can reduce SSR in the system.

کلیدواژه‌ها [English]

  • FACTS devices
  • Sub-synchronous resonance (SSR)
  • Fuzzy controller
  • Particle Swarm Optimization (PSO)
  • Artificial neural network (ANN)
[1] R. Pillay Carpanen, B.S. Rigby, "A contribution to modelling and analysis of SSSC-based power flow controls and their impact on SSR", Electric Power Systems Research, Vol. 88, pp. 98–111, July 2012.

[2] M.R. Alizadeh Pahlavani, H.A. Mohammadpour, "Damping of sub-synchronous resonance and low-frequency power oscillation in a series-compensated transmission line using gate-controlled series capacitor", Electric Power Systems Research, Vol. 81, No. 2, pp. 308–317, Feb. 2011.

[3] G. Shahgholian, E. Haghjoo, A. Seifi, I. Hassanzadeh, "The improvement DSTATCOM to enhance the quality of power using fuzzy-neural controller", Journal of Intelligent Procedures in Electrical Technology, Vol. 2, No. 6, pp. 3-16, Summer 2011 (in Persian).

[4] S.M. Abd-Elazim, E.S. Ali, "Synergy of particle swarm optimization and bacterial foraging for TCSC damping controller design", WSEAS Trans. on Power Systems, Vol. 8, No. 2, pp. 74-84, April 2013.

[5] A. Shoulaie, M. Bayati-PoudehG. Shahgholian, "Damping torsional torques in turbine-generator shaft by novel PSS based on genetic algorithm and fuzzy logic", Journal of Intelligent Procedures in Electrical Technology, Vol. 1, No. 2, pp. 3-10, Summer 2011. (in Persian).

[6] Z., Amini, A., Kargar, "Reduction of sub-synchronous resonance using DSSC", Proceeding of the Intelligent Systems Conference, 2014.

[7] D. Rai, S.O. Faried, G. Ramakrishna, A.A. Edris, "An SSSC-based hybrid series compensation scheme capable of damping subsynchronous resonance", IEEE Trans. on Power Delivery, Vol. 27, No. 2, pp.531-540, April 2012.

[8] J. Khazaie, M. Mokhtari, M. Khalilyan, D. Nazarpour, "Sub-synchronous resonance damping using distributed static series compensator (DSSC) enhanced with fuzzy logic controller", International Journal of Electrical Power and Energy Systems, Vol. 43, No. 1, pp. 80–89, Dec. 2012.

[9] D. RaiS.O. Faried, G. Ramakrishna, A.A. Edris, "An SSSC-based hybrid series compensation scheme capable of damping subsynchronous resonance", IEEE Trans. on Power Delivery, Vol. 27, No. 2, pp. 531-540, April 2012 (doi: 10.1109/TPWRD.2011.2175253)

[10] Z. Amini, A. Kargar, "Reduction of sub-synchronous resonance using artificial neural network", International Journal Multidisciplinary Sciences and Engineering, Vol. 4, No. 10, pp. 6-9, Nov. 2013.

[11] IEEE SSR Working Group, "Second benchmark model for computer simulation of of subsynchronous resonance", IEEE Trans. on Power Apparatus and Systems, Vol. PAS-104, No. 5, pp. 1057 – 1066, May 1985.

[12] R.G. Farmer, "Second benchmark model for computer simulation of subsynchronous resonance IEEE subsynchronous resonance working group of the dynamic system performance subcommittee power system engineering committee", IEEE Power Engineering Review,  Vol. PER-5, No. 5, May 1985.

[13] P. Fajri, S. Afsharnia, D. Nazarpour, M.A. Tavallaei, "Modeling simulation and group control of distributed static series compensators", American J. of Engineering and Applied Sciences, Vol. 1, No. 4, pp. 347-357, 2008.

[14] D. Divan, “Distributed intelligent power networks—A new concept for improving T&D system utilization and performance”, Proceeding of the IEEE/TDC, pp. 1–6, New Orleans, La, USA, April 2005.

[15] M. Rauls, "Analysis and design of high frequency co-axial winding transformers", MS Thesis, US: University of Wisconsin Madison, 1992.

[16] N.G. Hingorani, L. Gyugyi, "Understanding FACTS: Concepts and technology of flexible ac transmission system”, Wiley-IEEE Press, 2000.

[17] C.C. Lee, "Fuzzy logic in control systems: fuzzy logic controller", IEEE Trans. on Systems, Man, and Cybernetics, Vol. 20, No. 2, March/April 1990.

[18] M.S. Widyan, "On the effect of AVR gain on bifurcations of subsynchronous resonance in power systems", International Journal of Electrical Power and Energy Systems, Vol. 32, No. 6, pp. 656–663, July 2010.

[19] B.S. Nagabhushana, H.S. Chandrasekharaiah, "Analysis of SSR using artifical neural network", Proceeding of the IEEE/ISAP, pp. 416-420, Orlando, FL, Jan./Feb. 1996.