access icon free Evolutionary Prisoner's Dilemma in updating fuzzy linguistic model to damp power system oscillations

This study presents a novel technique to extract and update the rules of fuzzy linguistic model (FLM). The interrelations between inputs and outputs of a FLM are assigned using payoff matrix through Prisoner's Dilemma (PD). These interrelations are updated by updating the payoff matrix through Evolutionary Algorithm based PD to propose Evolutionary Algorithm based fuzzy Prisoner's Dilemma linguistic model (FPDLM). The effect of evolutionary algorithm based FPDLM as power system stabiliser is tested on single machine infinite bus system and also multi machine system.

Inspec keywords: power system stability; damping; evolutionary computation; oscillations; fuzzy set theory

Other keywords: payoff matrix; multi machine system; evolutionary algorithm based FPDLM; damp power system oscillations; fuzzy Prisoner’s Dilemma linguistic model; power system stabiliser; FLM; single machine infinite bus system

Subjects: Control of electric power systems; Optimisation techniques; Optimisation techniques; Combinatorial mathematics; Stability in control theory; Power system control; Combinatorial mathematics

References

    1. 1)
    2. 2)
      • 17. Kundur, P.: ‘Power system stability and control’ (McGraw-Hill, New York, 1994).
    3. 3)
    4. 4)
    5. 5)
      • 12. Fader, P.S., Hauser, J.R.: ‘Implicit coalitions in a generalized Prisoner's Dilemma’ (Sloan School of Management, 1987), pp. 188087.
    6. 6)
      • 19. Ross, T.J.: ‘Fuzzy logic with engineering applications’ (John Willey & Sons Ltd, 2004, 2nd edn.).
    7. 7)
      • 13. Kovacic, Z., Bogelan, S.: ‘Fuzzy controller design: theory and applications’ (CRC Press, 2006).
    8. 8)
      • 14. Tomescu, B.: ‘On the use of fuzzy logic to control paralleled dc-convertersDissertation, Virginia Polytechnic Institute and State University Blacksburg, Virginia, October 2001.
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • 20. Srikanth, N.V., Vinod Kumar, D.M.: ‘Investigation of stability of fuzzy logic based power system stabilizers using phase-plane analysis’. National Power Systems Conference (NPSC), 2004.
    13. 13)
      • 11. Szilagyi, M.N.: ‘An investigation of N-person Prisoners’ Dilemmas’ (Complex Systems, Complex Systems Publications, Inc, 2003 vol. 14), pp. 155174.
    14. 14)
      • 4. Rama Sudha, K., Vakula, V.S., Vijaya Shanthi, R.: ‘Particle swarm optimization in fine tuning of PID fuzzy logic power system stabilizerIEEE Computer Society Int. Conf. ACT 09 Trivandrum, 28th–29th 2009 IEEE, doi: 10.1109/ACT.2009.94.
    15. 15)
      • 5. Deng, H., Zhi, Y., Hu, H.: ‘Fuzzy strategy updating in the Prisoner's Dilemma game’, IJSSST, 13, (3A), pp. 1016.
    16. 16)
      • 15. Padmaja, A., Vakula, V.S., Padmavathi, T., Padmavathi, S.V.: ‘Small signal stability analysis using fuzzy controller and artificial neural networks stabilizer’, Int. J. Electr. Eng. Technol. (IJEET), 2010, 1, (1), pp. 3457.
    17. 17)
      • 7. Price, K.V., Storn, R.N., Lampinen, J.A.: ‘Differential evolution: practical approach to global optimization (Natural computing series)’ (Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005).
    18. 18)
      • 2. Hemmati, R., Mojtaba, S., Boroujeni, S., Abdollahi, M.: ‘Comparison of robust and intelligent based power system stabilizers’, Int. J. Phys. Sci., 2010, 5, (17), pp. 25642573.
    19. 19)
    20. 20)
      • 16. Padiyar, K.R.: ‘Power system dynamics; stability and control’ (B.S. Publications, 2008).
    21. 21)
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