GA Optimized AVR Controller with Higher Degree of Freedom of Tuning of Wanted Response
A genetic algorithm (GA) was used in this article to obtain optimal parameters of the automatic voltage regulator (AVR) which will assure the wanted response of the synchronous generator in all its working points of the capability diagram. From the third order mathematical model of the synchronous generator, equations which describe how gain and time constant of voltage dynamics of the synchronous generator change considering the working point are derived. A higher degree of freedom of tuning of the wanted response was achieved by two parameters which are overshoot and settling time of a reference model which describes the wanted dynamics of the excitation system. For one point of the capability diagram, analytical expressions of the optimal parameters of AVR are given for achieving the wanted response, while the optimal parameters of AVR which will assure minimal variation of responses of all working point of the capability diagram from the wanted response are obtained by using GA algorithm. Proposed GA optimized AVR which is realized by proportional and integrator (PI) controller was tested in a simulation by using the seventh and third order mathematical model and parameters of the synchronous generator of hydroelectric plant Peruća in Croatia.
Copyright © 2015 Praise Worthy Prize - All rights reserved.
V. Mukherjee, and S.P. Ghoshal, Intelligent particle swarm optimized fuzzy PID controller for AVR system, Electric Power Systems Research, Vol. 77(Issue 12):1689-1698, October 2007.
A. Oonsivilai, P. Pao-La-Or, Optimum PID Controller Tuning for AVR System Using Adaptive Tabu Search, Proceedings of the 12th WSEAS International Conference on Computers, pp. 987–992, Heraklion, Greece, July 2008.
A. Salem, M.A.M. Hassan, and M.E. Ammar, Tuning PID Controllers Using Artificial Intelligence Techniques Applied To DC-Motor and AVR System, Asian Journal of Engineering and Technology, Vol. 2(Issue 2):129-138, April 2014.
Z.-L. Gaing, A particle swarm optimization approach for optimum design of PID controller in AVR system, Energy Conversion, IEEE Transactions on, Vol. 19(Issue 2):384-391, June 2004.
I. Pan, and S. Das, Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization, International Journal of Electrical Power & Energy Systems, Vol. 51:106-118, October 2013.
J.-M. Kim, S.-I Moon, J. Lee, A new optimal AVR parameter tuning method using on-line performance indices of frequency-domain, Power Engineering Society Summer Meeting, Vol. 3, pp. 1554-1559, Vancouver, BC, Jul 2001.
B. Selvabala, D. Devaraj, Co-ordinated Design of AVR-PSS Using Multi Objective Genetic Algorithm (Springer, 2010, pp. 481-493).
H. Zhu, L. Li, Y. Zhao, Y. Guo, and Y. Yang, CAS algorithm-based optimum design of PID controller in AVR system, Chaos, Solitons & Fractals, Vol. 42(Issue 2):792-800, October 2009.
IEEE Std 421.5-2005, IEEE Recommended Practice for Excitation System Models for Power System Stability Studies, 2006.
P. Kundur, Power System Stability and Control (McGraw-Hill, 1994).
C.-T. Chen, Analog and Digital Control System Design: Transfer-Function, State-Space, and Algebraic Methods (Oxford, 2006).
I. Ilić, Z. Maljković, I. Gašparac, M. Pavlica, D. Ilić-Zubović, V. Jarić, A. Višković, and R. Belobrajić, Methodology for determining the actual PQ diagram of a hydrogenerator, Energija, Vol. 56(Issue 2):144-181, February 2007.
A.E. Eiben, J.E. Smith, Introduction to Evolutionary Computing (Springer, 2008).
D. Jolevski, and O. Bego, Input Shaping of the Synchronous Generator for Reduction of Self-induced Oscillations, Asian Journal of Control, 2015.
- There are currently no refbacks.
Please send any question about this web site to firstname.lastname@example.org
Copyright © 2005-2020 Praise Worthy Prize