A Robust PID Power System Stabilizer Design of Single Machine Infinite Bus System using Firefly Algorithm

Abstract

This paper presents the design of a proportional-integral-derivative power-system-stabilizer using the firefly algorithm for tuning of stabilizer parameters and washout (reset). The proposed optimization of parameters is carried out with eigenvalue analysis based objective function for two cases to guarantee the stability for the single-machine-infinite-bus system model for a wide range of operating conditions. The system performance with firefly algorithm tuned controller is compared with Bat-Algorithm optimized Conventional-Power-System-Stabilizer controller. The power system robustness is tested on 133 operating conditions. According to the eigenvalue analysis and time response parameters results, the FA-PID-PSS (case-II) can stabilize the system for all operating conditions.

Keywords

• “Conventional power system stabilizer”,“Firefly algorithm optimized proportional integral derivative based power system stabilizer (FA-PID-PSS)”,“Bat algorithm optimized conventional power system stabilizer (BA-CPSS)”

References

1. [1] Mohamed Kamari, N. A., Musirin, I., Othman, M. M. and Hamid, Z. A., “PSS-LL Based Power System Stability Enhancement Using IPSO Approach”, IEEE 7th International Power engineering and Optimization conference (PEOCO2013), 2013; Page(s): 658 - 663.
2. [2] Shubhanga, Dr. K. N., Yadi Anantholla, Mr. “Manual for A Multi-machine Small-signal Stability Program”, Version-1, India.
3. [3] Hingorani, N.G and Gyugyi, L., “Understanding FACTS”, IEEE press, NewYork, 2000. Page(s): (425–429).
4. [4] Abdul Jaleel, J., Thanvy, N., “A Comparative Study between PLPD,PID and Lead-Lag controllers for Power System Stabilizer” 2013 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2013], India, (2013).
5. [5] Demello, FP., Concordia, C. “Concepts of synchronous machine stability as affected by excitation control”. IEEE Trans Power Apparatus System 1969; PAS-88:316–29.
6. [6] Sebaa, K., Boudour, M., “Optimal locations and tuning of robust power system stabilizer using genetic algorithms”. Electr Power Syst Res 2009;79:406–16.
7. [7] Peng, Z., Malik, OP., “Design of an adaptive PSS based on recurrent adaptive control theory”. IEEE Trans Energy Convers,2009;24:884–92.
8. [8] Ramakrishna, G., Malik, OP., “Adaptive PSS using a simple on-line identifier and linear pole-shift controller”. Electrical Power Syst Res, 2010; 80:406–16.http:// dx.doi.org/10.1016/j.epsr.2009.10.004.

9. [9] Sambariya, D.K., Prasad, R., “Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm” Electrical Power and Energy Systems 61 (2014) 229–238, journal homepage.
10. [10] EKE,I., TAPLAMACIOĞLU, M. C. ve KOCA ARSLAN, I., “Power System Stabilizer Design for Rotor angle stability ”, International Journal of Engineering Research and Development, Vol.3, No.2, June 2011.
11. [11] Al-Duwaish, H.N., Al-Hamouz, Z.M., “A neural network based adaptive sliding mode controller: application to a power syst stabilizer”. Energy Convers Manage 2011; 52:1533-8.
12. [12] Soliman, M., Elshafei A.L., Bendary, F., Mansour, W. LMI., “Static output-feedback design of fuzzy Sower System Stabilizers”. Expert System Appl 2009; 36:6817–25.
13. [13] Mukherjee, V., Ghoshal, SP., “Intelligent particle swarm optimized fuzzy PID controller for AVR system”, Electrical Power System Res 2007; 77:1689–98.
14. [14] Bhati, PS., Gupta, R., “Robust fuzzy logic power system stabilizer based on evolution and learning”. Int J Electrical Power Energy System 2013; 53:357–66.
15. [15] Saoudi, K, Harmas, MN., “Enhanced design of an indirect adaptive fuzzy sliding mode power system stabilizer for multi-machine power systems”. Int. J. Electrical Power Energy System 2014 ;54:425–31.
16. [16] Ghasemi, A., Shayeghi, H., Alkhatib, H., “Robust design of multi-machine power system stabilizers using fuzzy gravitational search algorithm”. Int J. Electrical Power Energy System 2013; 51:190–200.
17. [17] Ramirez, JM., Correa, RE., Hernández, DC., “A strategy to simultaneously tune power system stabilizers”. Int J. Electrical Power Energy System 2012; 43:818–29.
18. [18] Nechadi, E., Harmas, MN., Hamzaoui, A., Essounbouli, N., “A new robust adaptive fuzzy sliding mode power system stabilizer”. Int J Electr Power Energy Sys 2012; 42:1-7. [19] Chaturvedi, DK., Malik, OP., “Neurofuzzy power system stabilizer”. IEEE Trans Energy Convers 2008;23:887–94.
19. [20] Awadallah, MA., Soliman, HM., “A neuro-fuzzy adaptive power system stabilizer using genetic algorithms”. Electr Power Compon Syst 2009; 37:158–73.
20. [21] Radaideh, SM., Nejdawi, IM., Mushtaha, MH., “Design of power system stabilizers using two level fuzzy and adaptive neuro-fuzzy inference systems”. Int J Electr Power Energy System 2012; 35:47–56.
21. [22] Gandhi, P.R., Joshi, S.K., “GA and ANFIS based Power SystemStabilizer” Power and Energy Society General Meeting (PES), 2013; Page(s): (1 – 5).
22. [23] Curtis, J., “Process control instrumentation technology”, Fourth Edition, PHI, 1998.
23. [24] Akkawi, A.R., Ali, M.H., Lamont, L.A., El Chaar, L., “Comparative Study between Various Controllers for Power System Stabilizer using Particle Swarm Optimization”, Electric Power and Energy Conversion Systems (EPECS), 2011 2nd Int. Conference on 2011; Page(s): (1 – 5).
24. [25] Khodabakhshian, A., Hemmati, R., “Multi-machine power system stabilizer design by using cultural algorithms”. Int J Electrical Power Energy System 2013; 44:571–80.
25. [26] Yang,X. S., “Nature-Inspired Metaheuristic Algorithms”, Luniver Press, UK, (2008).
26. [27] Agarwal, S., Singh, A.P., Anand, N., “Evaluation Performance Study of Firefly Algorithm, Particle Swarm Optimization and Artificial Bee colony algorithm for Non-Linear mathematical Optimization functions”, Computing, Communications and Networking Technologies (ICCCNT), 2013 4th Int. Conference on 2013 , Page(s): (1–8) .
27. [28] Yang, X. S., “Firefly algorithms for multimodal optimization”, Proc. 5th Symposium on Stochastic Algorithms, foundations and Applications, (Eds. O. Watanabe and T. Zeugmann), Lecture Notes in Computer Science, 5792: 169-178 (2009).
28. [29] Yang, X. S., “Engineering Optimisation: An Introduction with Metaheuristic Applica- tions”, John Wiley and Sons, USA (2010).
29. [30] Kundur, P., Power system stability and control. 12th reprint. New Delhi, India,Tata McGraw-Hill Education Pvt. Ltd. 2011.