Yıl: 2016 Cilt: 24 Sayı: 3 Sayfa Aralığı: 1150 - 1162 Metin Dili: İngilizce İndeks Tarihi: 29-07-2022

Performance analysis of biogeography-based optimization for automatic voltage regulator system

Öz:
A self-tuning method to determine the appropriate parameters of a proportional-integral-derivative controller for an automatic voltage regulator (AVR) system using a biogeography-based optimization (BBO) algorithm is proposed in this study. The BBO algorithm was developed based on the theory of biogeography, which describes migration and its results. We propose that the BBO algorithm has a high-quality solution and stable convergence characteristics, and thus it improves the transient response of the controlled system. The performance of the BBO algorithm depends on the transient response, root locus, and Bode analysis. Robustness analysis is done in the AVR system, which is tuned by an artificial bee colony (ABC) algorithm in order to identify its response to changes in the system parameters. We compare the BBO algorithm with the ABC algorithm, particle swarm optimization algorithm, and differential evolution algorithm. The results of this comparison show that the BBO algorithm has a better tuning capability than the other optimization algorithms.
Anahtar Kelime:

Konular: Mühendislik, Elektrik ve Elektronik
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • [1] Gozde H, Taplamacioglu MC. Comparative performance analysis of artificial bee colony algorithm for automatic voltage regulator (AVR) system. J Franklin Inst 2011; 348: 1927–1946.
  • [2] Mitra P, Maulik S, Chowdhury SP, Chowdhury S. ANFIS based automatic voltage regulator with hybrid learning algorithm. Int J Innovat Energy Syst Power 2007; 3: 397–401.
  • [3] Gaing ZL. A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE T Energy Convers 2004; 19: 384–391.
  • [4] Krohling RA, Rey JP. Design of optimal disturbance rejection PID controllers using genetic algorithm. IEEE T Evol Comput 2001; 5: 78–82.
  • [5] Coelho LS. Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach. Chaos Solitons Fractals 2009; 39: 1504–1514.
  • [6] Kim DH, Park JI. Intelligent PID controller tuning of AVR system using GA and PSO. In: International Conference on Intelligent Computing (ICIC); 23–26 August 2005; Hefei, China. pp. 366–375.
  • [7] Kim DH, Abraham A, Cho JH. A hybrid genetic algorithm and bacterial foraging approach for global optimization. Inform Sci 2007; 177: 3918–3937.
  • [8] Mukherjee V, Ghoshal SP. Intelligent particle swarm optimized fuzzy PID controller for AVR system. Electr Power Syst Res 2007; 77: 1689–1698.
  • [9] Zhu H, Li L, Zhao Y, Guo Y, Yang Y. CAS algorithm-based optimum design of PID controller in AVR system. Chaos Solitons Fractals 2009; 42: 792–800.
  • [10] Mohammadi SMA, Ghraveisi AA, Mashinchi M. New evolutionary method for optimal design of PID controllers for AVR system, In: 2009 IEEE Bucharest Power Tech Conference; 28 June–2 July 2009; Bucharest, Romania. pp.1–8.
  • [11] Simon D. Biogeography-based optimization. IEEE T Evol Comput 2008; 12: 702–713.
  • [12] Bhattacharya A, Chattopadhyay PK. Application of biogeography-based optimization for solving multi-objective economic emission load dispatch problem. Electr Power Compon Syst 2010; 38: 826–850.
  • [13] Panchal V, Singh P, Kaur N, Kundra H. Biogeography based satellite image classification. Int J Comput Sci Inf Secur 2009; 6: 269–274.
  • [14] Gupta S, Bhuchar K, Sandhu PS. Implementing Color Image Segmentation Using Biogeography Based Optimization. In: 2011 International Conference on Software and Computer Applications IPCSIT; 2011; Singapore. pp. 79–86.
  • [15] Rarick R, Simon D, Villaseca F, Vyakaranam B. Biogeography-based optimization and the solution of the power flow problem. In: Proceedings of the IEEE Conference on Systems, Man, and Cybernetics; 11–14 October 2009;San Antonio, TX, USA. pp. 1029–1034.
  • [16] Bhattacharya A, Chattopadhyay PK. Biogeography-based optimization for different economic load dispatch problems. IEEE T Power Syst 2010; 25: 1064–1077.
  • [17] Bhattacharya A, Chattopadhyay PK. Solving economic emission load dispatch problems using hybrid differential evolution. Appl Soft Comput 2011; 11: 2526–2537.
  • [18] Thomas G, Lozovyy P, Simon D. Fuzzy robot controller tuning with biogeography-based optimization. In: Proceedings of the 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems; 29 June–1 July 2011; Syracuse, NY, USA. pp. 319–327.
  • [19] Song Y, Liu M, Wang Z. Biogeography-based optimization for the traveling salesman problems. In: 2010 Third International Joint Conference on Computational Science and Optimization; 28–31 May 2010; Huangshan, China.pp. 295–299.
  • [20] Naderi F, Gharaveisi AA, Rashidinejad M. Optimal design of type 1 TSK fuzzy controller using GRLA for AVR system. In: 2007 Large Engineering Systems Conference on Power Engineering; 10–12 October 2007; Montreal,Canada. pp. 106–111.
  • [21] Xue D, Chen Y. Atherton D. Linear feedback control: analysis and design with MATLAB. Philadelphia, PA, USA: SIAM Press, 2007.
  • [22] Lin Y, Ang KH, Chong GCY. PID control system analysis and design. IEEE Control Syst Mag 2006; 26: 32–41.
  • [23] Du D, Simon D, Ergezer M. Biogeography-based optimisation combined with evolutionary strategy and immigration refusal. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics; 11–14 October 2009; San Antonio, TX, USA. pp. 997–1002.
  • [24] Roy PK, Ghoshal SP, Thakur SS. Combined economic and emission dispatch problems using biography-based optimization. Electr Eng 2010; 92: 173–184.
  • [25] Simon D. A dynamic system model of biogeography-based optimization. Appl Soft Comput 2011; 11: 5652–5661.
  • [26] Tay TT, Mareels I, Moore JB. High Performance Control. New York, NY, USA: Springer-Verlag, 1997.
APA GÜVENÇ U, Yigit T, ISIK A, AKKAYA İ (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. , 1150 - 1162.
Chicago GÜVENÇ UĞUR,Yigit Tuncay,ISIK ALI HAKAN,AKKAYA İbrahim Performance analysis of biogeography-based optimization for automatic voltage regulator system. (2016): 1150 - 1162.
MLA GÜVENÇ UĞUR,Yigit Tuncay,ISIK ALI HAKAN,AKKAYA İbrahim Performance analysis of biogeography-based optimization for automatic voltage regulator system. , 2016, ss.1150 - 1162.
AMA GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ Performance analysis of biogeography-based optimization for automatic voltage regulator system. . 2016; 1150 - 1162.
Vancouver GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ Performance analysis of biogeography-based optimization for automatic voltage regulator system. . 2016; 1150 - 1162.
IEEE GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ "Performance analysis of biogeography-based optimization for automatic voltage regulator system." , ss.1150 - 1162, 2016.
ISNAD GÜVENÇ, UĞUR vd. "Performance analysis of biogeography-based optimization for automatic voltage regulator system". (2016), 1150-1162.
APA GÜVENÇ U, Yigit T, ISIK A, AKKAYA İ (2016). Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences, 24(3), 1150 - 1162.
Chicago GÜVENÇ UĞUR,Yigit Tuncay,ISIK ALI HAKAN,AKKAYA İbrahim Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences 24, no.3 (2016): 1150 - 1162.
MLA GÜVENÇ UĞUR,Yigit Tuncay,ISIK ALI HAKAN,AKKAYA İbrahim Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences, vol.24, no.3, 2016, ss.1150 - 1162.
AMA GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences. 2016; 24(3): 1150 - 1162.
Vancouver GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ Performance analysis of biogeography-based optimization for automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences. 2016; 24(3): 1150 - 1162.
IEEE GÜVENÇ U,Yigit T,ISIK A,AKKAYA İ "Performance analysis of biogeography-based optimization for automatic voltage regulator system." Turkish Journal of Electrical Engineering and Computer Sciences, 24, ss.1150 - 1162, 2016.
ISNAD GÜVENÇ, UĞUR vd. "Performance analysis of biogeography-based optimization for automatic voltage regulator system". Turkish Journal of Electrical Engineering and Computer Sciences 24/3 (2016), 1150-1162.