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International Symposium on Neural Networks

ISNN 2005: Advances in Neural Networks – ISNN 2005 pp 668–673Cite as

Adaptive Neuro-fuzzy SVC for Multimachine Hybrid Power System Stability Improvement with a Long of Double Circuit Transmission Lines

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3498))

Abstract

This paper presents the development of Neuro-Fuzzy Static Var Compen-sator (SVC)for the purpose of improving power system stability with a long of double circuit transmission lines system. The proposed control method, Neuro-Fuzzy Logic Static Var Compensator based on proportional integral information for the purpose of power system stability improvement. The test system is a two area multimachine hybrid power system consisting of 2 synchronous generators and 2 induction generat-ors connected to an infinite bus through a double circuit transmission line with SVC located at the midpoint. The SVC is installed at the transmission line that is linked between two power system areas. The input signal of fuzzy controller is the power flowing in the transmission line connected to the SVC bus. The simulation results demonstrate the good response of this proposed control. Comparison results of stabi-lity control between the conventional method of power system stabilizer (PSS)and the PSS with SVC controlled by fuzzy of a long distance power transmission system.

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References

  1. Hongesombut, K., Leelajindakrairerk, M.: Genetic Algorithm Aided Fuzzy Controller Design of SVC for Improving Power System Stability. Ladkrabang Engineering Journal 16, 31–36 (1999)

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  4. Hongesombut, K., Leelajindakrairerk, M.: FLSVC Based on PI Information for Power System Stability Improvement With A Long Transmission Line System. In: 22st Electrical Engineering Conference, pp. 208–211 (1999)

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Faculty of Engineering, Kasem Bundit University, Bangkok, Thailand

    Chamni Jaipradidtham

Authors
  1. Chamni Jaipradidtham
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Jaipradidtham, C. (2005). Adaptive Neuro-fuzzy SVC for Multimachine Hybrid Power System Stability Improvement with a Long of Double Circuit Transmission Lines. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_106

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  • DOI: https://doi.org/10.1007/11427469_106

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25914-5

  • Online ISBN: 978-3-540-32069-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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