AN ADAPTIVE POWER SYSTEM STABILIZER BASED ON FOCUSED TIME DELAY NEURAL NETWORK

https://doi.org/10.22146/teknosains.35130

Widi Aribowo(1*)

(1) State University Of Surabaya
(*) Corresponding Author

Abstract


In this paper, Power System Stabilizer is designed in Single Machine Infinite Bus (SMIB) and speed control is implemented with a dynamic topology based on Focused Time Delay Neural Network (FTDNN).  In case of prediction and control, two individual strategies are concerned for the current projects. The first is identification the dynamics of system. The other is an optimization unit expected for minimization disturbances. The performance of the system with FTDNN-PSS controller is compared with a Conventional PSS (C-PSS), RNN-PSS and DTDNN PSS. The results show the effectiveness of FTDNN-PSS design, and superior robust performance for enhancement power system stability compared to Conventional PSS with different cases.


Keywords


SMIB, PSS, FTDNN, DTDNN, Single machine

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References

Kundur P, Balu NJ, Lauby MG. 1994. Power system stability and control. New York: McGraw-Hill.

Sauer P, Pai M. 1998. Power system dynamics and stability. Upper Saddle River, NJ: Prentice-Hall.

K. Karthikeyan, P. Lakshmi. 2012. "Optimal Design of PID Controller for Improving Rotor Angle Stability using BBO".Procedia Engineering, 38:889-902.

Ibrahim, L. M. 2010. “Anomaly network intrusion detection system based on distributed time-delay neural network (DTDNN)”. Journal of Engineering Science and Technology, 5:457–471

Aribowo,W. 2010. “Stabilisator Sistem Tenaga Berbasis Jaringan Syaraf Tiruan Berulang Untuk Sistem Mesin Tunggal”. Journal Of Telecommunication, Computing, Electronics and Control, Vol 8,No 1: 65-72. http://dx.doi.org/10.12928/telkomnika.v8i1.606.

MATLAB 7.6.0 (R2008a) Neural Network Toolbox Software.

Olaru, A., Olaru, S., Paune, D., Oprean, A. 2011. “Optimisation Of The Space Control Trajectory With Proper Neural Network And Lab View Instrumentation”. HARVEX 2011 Proceeding, ISSN 1454 – 8003. 167-191.

Xu D, and He R. 2002. “ANN Based Multiple Power System Stabilizers Adaptive and Coordinates Control”. PowerCon 2002. International Conference Proceeding. 2002; 1: 361-364.

Rogers GY.(2000) The application of Power System Stabilizers to a Multigenerator Plant. IEEE Trans. Power System; 15(1): 350–355.

Chen CJ, Chen TC. 2007. “Design of a Power System Stabilizer using a New Recurrent Network”. International Journal of Innovative Computing, Information and Control, 3(4): 907918.

You R, Eghbali HJ, Nehrir M. 2003. “An Online Adaptive Neuro-Fuzzy Power System Stabilizer for Multi-machine Systems”. IEEE Transaction on Power Systems.18(1): 128-135.

Chaturvedi DK, Malik OP. 2004. “Neural Network Controller for Power System Stabilizer”. Journal of the Institution of Engineers. 85(1): 138-145.

Lin CH. 2004.”Adaptive Recurrent Fuzzy Neural Network Control for Synchronous Reluctance Motor Servo Drive”. IEE Proc. Power Applications.151(6): 711-724.

https://doi.org/10.1049/ip-epa:20040687

J. He and O. P. Malik.1997. “An Adaptive Power System Stabilizer Based on Recurrent Neural Networks”, IEEE Trans. Energy Conversion, Vol. 12, No. 4, ,pp.413-419

Olaru, A., Olaru S., Ciupitu, L. 2010. “Assisted research of the neural network by bach propagation algorithm”. OPTIROB 2010 International Conference, Calimanesti, Romania, The RPS Singapore Book, pp. 194-200.

Olaru, A., Olaru, S., Paune D., Ghionea A. 2010. “Assisted research of the neural network”. OPTIROB 2010 International Conference, Calimanesti, Romania, The RPS Singapore Book, pp. 189-194.

Olaru, A., Olaru, S. 2010. “Assisted research of the neural network with LabVIEW instrumentation”. IEEE ICMENS2010 Proceedings, Changsha, China, pp. 1-8.

Olaru, A., Oprean, A., Olaru, S., Paune, D. 2010. “Optimization of the neural network by using the LabVIEW instrumentation”. IEEE ICMERA 2010 Proceedings, ISBN 978-1-4244-8867-4, IEEE catalog number CFP1057L-ART, pp. 40-44.

Olaru, A., Olaru, S., Paune, D.2010. “Assisted research dynamic neural network with time delay and recurrent links”. IEEE ICMERA 2010 Proceedings, ISBN 978-1-4244-8867-4, IEEE catalog number CFP1057L-ART, pp. 284-288.

Olaru, A., Olaru, S., Paune, D., Oprean, A.2011.” Assisted Research and Optimization of the proper Neural Network Solving the Inverse Kinematics Problem”. IACSIT OPTIROB 2011 Proceedings, ISSN 2010-460X, ISBN 978-981-108-8906-7, pp.15-23.

Katsuhiko Ogata. 2002. Modern Control Engineering, Univercity of Minnesota, Prentice-Hall.

Glover, Sarma. 2002. Power System Analysis and Design. Third Edition. Wadsworth Group. adivision of Thomson Learning,Inc.



DOI: https://doi.org/10.22146/teknosains.35130

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