Improvement of Synchronous Machine Dynamic Characteristics via Neural Network Based Controllers

Authors: S. A. Gawish, F. A. Khalifa, R. M. Mostafa

Abstract:

This paper presents Simulation and experimental study aimed at investigating the effectiveness of an adaptive artificial neural network stabilizer on enhancing the damping torque of a synchronous generator. For this purpose, a power system comprising a synchronous generator feeding a large power system through a short tie line is considered. The proposed adaptive neuro-control system consists of two multi-layered feed forward neural networks, which work as a plant model identifier and a controller. It generates supplementary control signals to be utilized by conventional controllers. The details of the interfacing circuits, sensors and transducers, which have been designed and built for use in tests, are presented. The synchronous generator is tested to investigate the effect of tuning a Power System Stabilizer (PSS) on its dynamic stability. The obtained simulation and experimental results verify the basic theoretical concepts.

Keywords: Adaptive artificial neural network, power system stabilizer, synchronous generator.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1329442

References:

[1] Anderson P. M. and Fouad A. A., ' Power System Control Stability", Vol.1, The Iowa State University press, 1977.
[2] IEEE Working Group on Prime Mover and Energy Supply Models for System Dynamic Performance Studies. "Hydraulic Turbine and Yurbine Control Models for Dynamic Studies". IEEE Trans. On Power Systems, Vol. 7, No. 1, Fep.1992, PP.167-179
[3] "Recommended Practice for Excitation System Modeles for Power System Stability Studies ". IEEE Standards 421.5-1992, August 1992.
[4] Hassan Bevarni, Takashi hiyama and yasunori mitani,'' Power System Dynamic Stability and voltage Regulation Enhancement Using an Optimal Gain Vector." Control Engineering Practice, Jan., 2008. Available at WWW. Science direct. Com
[5] Y Zhang, G. P. Chen, O. P. Malik and G. S. Hope, "An Artificial Neural Network Based Power System Stabilizer ", IEEE Trans. On Energy Conv., Vol.8, No.1, PP 71-77, March 1993.
[6] Shiji Cheng, Rujing Zhou and Lin Guan, "An on - line self-Learning Power System Stabilizer using a neural network method", IEEE Trans. Power System. Vol. 12, No.2, May 1997.
[7] S. Chusanapiputt and K. Withirom present," Parameter tuning of the conventional power system stabilizer by Artificial Neural Network.", Conf.on Power System Technology, 2004, Bangkok, Thailand.
[8] Wenxin liu and Ganesh K. Venayagamorthy,'' Design of an Adaptive neural network Based power system stabilizer." Neural networks, Vol.16, June - July 2003, p.p.891-898.
[9] Jesus Fraile - Ardanvy, P.J. Zufiria," Design and comparison of Adaptive Power system stabilizers Based on Neural Fuzzy Networks and Genetic Algorithms." Neurocomputing, Vol.70, Oct.2007 pp. 2902- 2912.
[10] P. Shamsollahi and O.P. Malik, "Design of a Neural Adaptive power system Using Dynamic Back - Propagation Method.", Int. Journal of Elect. Power & Energy systems, Vol.22, Jan. 2000 PP.29-34.