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Optimal Tuning of Multi-machine Power System Stabilizer Parameters Using Grey Wolf Optimization (GWO) Algorithm

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Emerging Trends in Electrical, Communications, and Information Technologies

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 569))

Abstract

Optimal tuning of Power System Stabilizers (PSSs) parameters using Grey Wolf Optimization (GWO) algorithm is presented in this paper. Selection of the parameters of power system stabilizers which simultaneously stabilize system oscillations is converted to a simple optimization problem which is solved by a Grey Wolf Optimization (GWO) algorithm. The efficiency of the proposed method has been tested on two cases of multi-machine systems include 3-machine 9 buses system. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and at the same time guarantees a robust acceptable performance over a wide range of operating and system condition.

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References

  1. Demello FP, Concordia C (1969) Concept of synchronous machine stability as affected by excitation control. IEEE Trans PAS 88:316–329

    Article  Google Scholar 

  2. Larsen EV, Swann DA (1981) Applying power system stabilizers, Part I–III. IEEE Trans PAS 100(6):3017–3046

    Article  Google Scholar 

  3. Kundur P (1993) Power system stability and control. McGraw Hill Inc

    Google Scholar 

  4. Yu YN (1983) Electric power system dynamics. Academic Press

    Google Scholar 

  5. Kundur P, Klein M, Rogers GJ, Zywno MS (1989) Applications of power system stabilizers for enhancement of overall system stability. IEEE Trans PAS 4(2):614–626

    Google Scholar 

  6. Cheng S, Malik OP, Hope GS (1986) Design of self-tuning PID stabilizer for a multimachine power system. IEE Proc Part C 133(4):176–185

    Google Scholar 

  7. Hsu YY, Liou KL, Hsu YY, Cheng CV (1990) Design of fuzzy power system stabilizers for multimachine power systems. IEE Proc Part C 137(3)

    Article  Google Scholar 

  8. Zhang Y, Chen GP, Malik OP, Hope GS (1993) An artificial neural based adaptive power system stabilizer. IEEE Trans Energy Convers 8(1):71–77

    Article  Google Scholar 

  9. Zhang Y, Malik OP, Chen GP (1995) Artificial neural network power system stabilizers in multi-machine power system environment. IEEE Trans Energy Convers 10(1):147–154

    Article  Google Scholar 

  10. Goldberge DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley Publishing Company Inc

    Google Scholar 

  11. Abdel-Magid YL, Bettayeb M, Dawoud MM (1997) Simultaneous stabilization of power systems using genetic algorithm. In: IEE proceedings-generation, transmission and distribution, vol 144, no 1

    Article  Google Scholar 

  12. Abido MA, Abdel-Mazid YL (1998) A genetic-based power system stabilizer. Electr Mach Power Syst 26:559–571

    Article  Google Scholar 

  13. Abido MA, Abdel-Magid YL (1999) Hybridizing rule-based power system stabilizers with genetic algorithms. IEEE Trans Power Syst 14:600–607

    Article  Google Scholar 

  14. Afzalian, Linkens DA (2000) Training of neuro-fuzzy power system stabilizers using genetic algorithms. Electr Power Energy Syst 22:93–102

    Article  Google Scholar 

  15. Lakshmi P, Abdullah Khan M (2000) Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm. Electr Power Energy Syst 22:130–145

    Article  Google Scholar 

  16. Wang YP, Watson NR, Chong HH (2002) Modified genetic algorithm to design of an optimal PID controller for AC-DC transmission systems. Int J Electr Power Energy Syst 24:59–69

    Article  Google Scholar 

  17. Andreoiu A, Bhattacharya K (2002) Robust tuning of power system stabilizers using a Lyapunov method based genetic algorithm. In: IEE proceedings on generation, transmission and distribution, vol 149, no 5, September 2002, pp 585–592, Gainesville, Florida, 2007, pp 162–173

    Article  Google Scholar 

  18. Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69(1):46–61

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. EEE Department, JNTUA, Anantapur, 515002, Andhra Pradesh, India

    P. Dhanaselvi & R. Kiranmayi

  2. EEE Department, NBKRIST, Nellore, 524413, Andhra Pradesh, India

    S. Suresh Reddy

Authors
  1. P. Dhanaselvi
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  2. S. Suresh Reddy
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  3. R. Kiranmayi
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Corresponding author

Correspondence to P. Dhanaselvi .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur, Andhra Pradesh, India

    T. Hitendra Sarma

  2. Department of Electrical Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India

    V. Sankar

  3. Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Rafi Ahamed Shaik

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Cite this paper

Dhanaselvi, P., Suresh Reddy, S., Kiranmayi, R. (2020). Optimal Tuning of Multi-machine Power System Stabilizer Parameters Using Grey Wolf Optimization (GWO) Algorithm. In: Hitendra Sarma, T., Sankar, V., Shaik, R. (eds) Emerging Trends in Electrical, Communications, and Information Technologies. Lecture Notes in Electrical Engineering, vol 569. Springer, Singapore. https://doi.org/10.1007/978-981-13-8942-9_29

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  • DOI: https://doi.org/10.1007/978-981-13-8942-9_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-8941-2

  • Online ISBN: 978-981-13-8942-9

  • eBook Packages: EngineeringEngineering (R0)

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