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Neural Controller for Damping Transmission Line Oscillations


  • Department of Electrical and Electronics Engineering, SCSVMV University, Enathur, Kanchipuram - 631561, Tamil Nadu, India


Objective: This paper presents how a neural controller negotiates and dampen the oscillations, due to a transient fault that occurs in a power system. Methods/ Analysis: In this research work a transient symmetrical fault and its associated damping are analyzed, the response of the two controllers, one is the fuzzy tuned controller and the other controller is designed with neural logic for maneuvering momentary fault condition. Thyristor Controlled Reactor is a potential controller used for reactance control and for damping the oscillations in power system. Findings: Through this research article the effect of TCR is analyzed. In the present flexible A.C transmission system TCR is used for damping oscillations in the transmission line caused due to disturbance. Here, a symmetrical fault is simulated and the results are presented. Neural tuning of TCR improvises the result. Even without tuning TCR has the property of damping line oscillations, if tuned in a proper way by intelligent controllers definitely it has improvisation over the results. Novelty/improvement: The main novelty here is the use of neural controller for tuning a TCR. Generally, earlier the outputs were obtained through fuzzy controller or PID controllers. Also here the outputs are analyzed for three phases.


Fault Analysis, Fuzzy, Mat-lab, Neural, TCR.

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  • Ashokkumar N, Rathinakumar M. Intelligent solution for transmission line management for three phase to ground fault problems. International Review of Automatic Control. 2014 Sep; 7(5).
  • Santamaria J. Analysis of power systems under fault conditions. B. S. Universidad Centroamericana, Elsalvador; 2006.
  • Available from:
  • Giri PD, Shah SK. Fuzzy logic controller and neural network controller as a power system regulator implemented on GUI. Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011), 2011 Dec 20–22, Vol 30 of the series Advances in Intelligent and Soft Computing; 2011. p. 243–56.
  • Dash K, Liew AC, Mirshra BR. An adaptive PID stabilizer for power systems using fuzzy logic control. Electric Power Systems Research. 1998 Mar; 44(3):213–22.
  • Filip I, Prostean O, Vasar C, Szeidert I. Adaptive fuzzy controller for synchronous generator. 3rd Romanian Hungarian Joint Symposium on Applied Computational Intelligence (SACI), Timisoara Romania; 2006 May.
  • El-Hawary, Mohamed E. Electric power applications of fuzzy systems. Wiley-IEEE Press; 1988.
  • Tomescu B. On the use of fuzzy logic to control paralleled dc-dc converters. Dissertation Virginia Polytechnic Institute and State University Blacksburg, Virginia; 2001 Oct.
  • Hasan AR, Martis TS, SadralUla AHM. Design and implementation of a fuzzy controller based automatic voltage regulator for synchronous generator. IEEE Transactions on Energy Conversion. 1994; 9(3):451–9.
  • Visioli A, Nagrath IJ, Gopal M. Tuning of PID controllers with fuzzy logic. Control Systems Engineering; 1999.
  • Yolac U, Yalcinoz T. Comparison of fuzzy logic and PID controllers for TCSC using MATLAB. 39th International Conference on Universities Power Engineering. 2004 Sep; 1:438–42.
  • Static VAR Compensator. Available from:
  • Ghafori A, Zolghadri MR, Ehsan M. Fuzzy controlled STATCOM for improving the power system transient stability. IEEE International Conference on Power System; 2001. p. 1178–85.
  • Radman G, Raje RS. Dynamic model for power systems with multiple FACTS controllers. Electric Power Systems Research; 2008. p. 361–71.
  • Midhulananthan N. Canizares CA. Comparison of PSS, SVC and STATCOM controllers for damping power system oscillations. IEEE Transactions on Power Systems. 2003 May; 18(2).
  • Miranda V. An improved fuzzy inference system for voltage / VAR control. IEEE Transactions on Power Systems. 2007 Nov; 22(4).
  • Athay T, Podmore R, Virmani S. A robust control strategy for shunt and series reactive compensators to damp electromechanical oscillations. IEEE Transactions on Power Delivery. 2001 Oct; 16(4):812–17.
  • Hoang P, Tomsovic K. Design and analysis an adaptive fuzzy power system stabilizer. IEEE Transactions on Energy Conversion. 1996 Jun; 11(2).
  • Ibrahim HEA, Mahmoud AAH. DC motor control using PID controller based on improved ant colony algorithm. International Review of Automatic Control (IREACO). 2014; 7(1):1–6.
  • Chafaa K, Benzid R, Slimane N, Ghanai M, Blanco D, Moreno L. Type-2 fuzzy basis functions for adaptive control. International Review of Automatic Control (IREACO). 2013; 6(1):14–18.
  • Singh R, Singh AK. Design and comparison of a PI and PID controller for effective active and reactive power control in a grid connected two level VSC. International Review of Automatic Control. 2013; 6(6):759–66.
  • Saghafinia A, Ping HW, Rahman MA. High performance induction motor drive using hybrid fuzzy-PI and PI controllers. A International Review of Electrical Engineering. 2010; 5(5):2000–2011.
  • Duman S, Ozturk A. Robust design of PID controller for power system stabilization by using real coded genetic algorithm. International Review of Electrical Engineering. 2010 Sep; 5(5).
  • Banaei MR. Tuning of damping controller parameters using multi-objective PSO algorithm for STATCOM. International Review of Electrical Engineering. 2011; 6(1):300–8.
  • Abedinia O, Naderi MS, Jalili A, Mokhtarpour A. A novel hybrid GA-PSO technique for optimal tuning of fuzzy controller to improve multi-machine power system stability. International Review of Electrical Engineering. 2011; 6(2).
  • Kasilingam G, Pasupuleti J. Coordination of PSS and PID controller for power system stability enhancement – overview. Indian Journal of Science and Technology. 2015 Jan; 8(2):142–51. DOI: 10.17485/ijst/2015/v8i2/58441.
  • Sujatha S, Anita R, Selvan P, Selvakumar S. Impact of static VAR compensator in stability and harmonics mitigation for real time system with cogeneration. Indian Journal of Science and Technology. 2015 Jun; 8(12). DOI: 10.17485/ijst/2015/v8i12/54007.


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