Improvement of Synchronous Machine Dynamic Characteristics via Neural Network Based Controllers
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.
[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.
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:50130", author = "S. A. Gawish and F. A. Khalifa and R. M. Mostafa", title = "Improvement of Synchronous Machine Dynamic Characteristics via Neural Network Based Controllers", 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.", volume = "2", number = "5", pages = "742-7", }