FUZZY RULE TABLE OPTIMIZATION OF POWER SYSTEM STABILIZER USING GENETIC ALGORITHM

Öz

This paper investigated the rule table optimization of fuzzy power system stabilizer (FPSS) benefiting from rule basis of related previous studies. In the previous studies, fuzzy rules for Power System Stabilizer (PSS) were obtained by trial and error according to the experience of experts. There were a few rule tables occurred in that way in the literature. In this subject field, five rule tables with a few differences among them were taken. Genetic algorithm (GA) was employed as an optimization method, and single machine infinite bus (SMIB) model was used for simulation system. This work proposed to contribute optimization performance of FPSS adding these rule tables to the initial population of GA. Thus GAs reached an optimum solution more quickly. Simulation studies and ITAE performance results for four loading conditions were shown. The effectiveness of the proposed approach was discussed by comparing it with the five rule tables.

Anahtar Kelimeler

• Power system stabilizer,optimization,fuzzy control,rule table,genetic algorithm

Kaynakça

1. Lu, J., Nehrir, M.H. and Pierre, D.A., “A fuzzy logic-based adaptive power system stabilizer for multi-machine systems,” Electr. Power Syst. Res., vol. 60, no. 2, pp. 115–121, 2001. doi:10.1109/PESS.2000.867421
2. Bouchama, Z. and Harmas, M.N., “Optimal robust adaptive fuzzy synergetic power system stabilizer design,” Electr. Power Syst. Res., vol. 83, no. 1, pp. 170–175, Feb. 2012. doi:10.1016/j.epsr.2011.11.003
3. Wang, S.K. “Coordinated parameter design of power system stabilizers and static synchronous compensator using gradual hybrid differential evaluation,” Int. J. Electr. Power Energy Syst., vol. 81, pp. 165–174, Oct. 2016. doi:10.1016/j.ijepes.2016.02.016
4. Mitra, P., Chowdhury, S., Chowdhury, S.P., Pal, S.K., Lahiri, R.N. and Song, Y.H., “Performance of A Fuzzy Power System Stabilizer With Tie Line Active Power Deviation Feedback,” 2006 IEEE PES Power Syst. Conf. Expo., pp. 884–889, 2006. doi:10.1109/PSCE.2006.296431
5. Malik, O.P., “A Fuzzy Logic Based PSS Using a Standardized Rule Table,”, Electric Machines & Power Systems, Volume 27, Issue 3, pp. 295–310, 1999. doi:10.1080/073135699269316
6. Hwang, G-H., Kim, D-W., Lee, J-H. and An, Y-J., “Design of fuzzy power system stabilizer using adaptive evolutionary algorithm,” Eng. Appl. Artif. Intell., vol. 21, no. 1, pp. 86–96, 2008. doi:10.1016/j.engappai.2006.11.008
7. Mrad, F., Karaki, S. and Copti, B., “A novel fuzzy logic synchronous machine stabilizer,” IAS ’97. Conf. Rec. 1997 IEEE Ind. Appl. Conf. Thirty-Second IAS Annu. Meet., vol. 2, pp. 797–803. doi:10.1109/IAS.1997.628953
8. Cheng Y. and Elangovan, S., “Enhanced power system stabilizer via integrated tabu–fuzzy knowledge based controller,” Int. J. Electr. Power Energy Syst., vol. 25, no. 7, pp. 543–550, 2003. doi:10.1016/S0142-0615(02)00160-6

9. Safaee B. and Mashhadi, S.K.M., “Fuzzy membership functions optimization of fuzzy controllers for a quad rotor using particle swarm optimization and genetic algorithm,” in 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA), 2016, vol. 7, pp. 256–261. doi:10.1109/ICCIAutom.2016.7483170
10. Caner, M., Umurkan, N., Tokat, S. and Üstün, S.V., “Determination of optimal hierarchical fuzzy controller parameters according to loading condition with ANN,” Expert Syst. Appl., vol. 34, no. 4, pp. 2650–2655, 2008. doi:10.1016/j.eswa.2007.05.038
11. Abido, M.A. and Abdel-Magid, Y.L., “A hybrid neuro-fuzzy power system stabilizer for multimachine power systems,” IEEE Trans. Power Syst., vol. 13, no. 4, pp. 1323–1330, 1998. doi:10.1109/59.736272
12. Hongesombut, K. and Mitani, Y., “Implementation of Advanced Genetic Algorithm to Modern Power System Stabilization Control,” pp. 1–6. doi:10.1109/PSCE.2004.1397451
13. Lakshmi, P. and Abdullah Khan, M., “Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm,” Int. J. Electr. Power Energy Syst., vol. 22, no. 2, pp. 137–145, Feb. 2000. doi:10.1016/S0142-0615(99)00043-5
14. Hassan, L. H., Moghavvemi, M., Almurib, H. A. F., Muttaqi, K. M. and Ganapathy, V. G., “Optimization of power system stabilizers using participation factor and genetic algorithm,” Int. J. Electr. Power Energy Syst., vol. 55, pp. 668–679, Feb. 2014. doi:10.1016/j.ijepes.2013.10.026
15. J. Fraile-Ardanuy and P. J. Zufiria, “Adaptive power system stabilizer using ANFIS and genetic algorithms,” Proc. 44th IEEE Conf. Decis. Control. Eur. Control Conf. CDC-ECC ’05, vol. 2005, pp. 8028–8033, 2005. doi:10.1109/CDC.2005.1583461
16. Dawoud, M.M., “Simultaneous stabilisation of power systems using genetic algorithms,” Transm. Distrib. (former title), pp. 39–44. doi:10.1049/ip-gtd:19970785
17. Abdel-Magid, Y.L., Abido, M.A., Al-Baiyat, S. and Mantawy, A. H., “Simultaneous stabilization of multimachine power systems via genetic algorithms,” IEEE Trans. Power Syst., vol. 14, no. 4, pp. 1428–1439, 1999. doi:10.1109/59.801907
18. Abido M.A., and Abdel-Magid, Y. “A Genetic-Based Power System Stabilizer,” Electr. Mach. Power Syst., vol. 26, no. 6, pp. 559–571, 1998. doi:10.1080/07313569808955841
19. Fraile-Ardanuy J. and Zufiria, P.J., “Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms,” Neurocomputing, vol. 70, no. 16–18, pp. 2902–2912, 2007. doi:10.1016/j.neucom.2006.06.014
20. Demello, F.P. and Concordia, C., “Concepts of Synchronous Machine Stability as Affected by Excitation Control,” IEEE Trans. Power Appar. Syst., vol. PAS-88, pp. 316–329, 1969. doi:10.1109/TPAS.1969.292452
21. El-Zonkoly, A.M., “Optimal tuning of power systems stabilizers and AVR gains using particle swarm optimization,” Expert Syst. Appl., vol. 31, no. 3, pp. 551–557, 2006. doi:10.1016/j.eswa.2005.09.061
22. Gupta R. Bandyopadhyay, B. and Kulkarni, A. M. “Design of power system stabilizer for single machine system using robust fast output sampling feedback technique,” Electr. Power Syst. Res., vol. 65, no. 3, pp. 247–257, 2003. doi:10.1016/S0378-7796(03)00017-8
23. Iruthayarajan, M. W. and Baskar, S., “Evolutionary algorithms based design of multivariable PID controller,” Expert Syst. Appl., vol. 36, no. 5, pp. 9159–9167, 2009. doi:10.1016/j.eswa.2008.12.033