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PSO Based Tuning of a Integral and Proportional Integral Controller for a Closed Loop Stand Alone Multi Wind Energy System

  • L. V. Suresh KumarEmail author
  • G. V. Nagesh Kumar
  • D. Anusha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 410)

Abstract

The summary of the paper explains the optimal tuning of integral (I) and proportional integral (PI) controllers are applied to closed loop standalone integrated multi wind energy system by using particle swarm optimization. Tuning of I and PI controller gain values obtained from the optimization techniques to get the best possible operation of the system. For the optimal performance of the integrated wind energy system, the controller gains are tuned by using the PSO and genetic algorithms (GA). The system harmonics of voltage responses are observed with search heuristic algorithm that is nothing but a genetic algorithm. Similarly the system responses are observed and compared with PSO algorithm, and the PSO algorithm is proved better. The results establishes the proposed new stand alone multi wind energy system with I, PI controller gains are tuned by using PSO will gives less harmonic distortion and improves performance. The proposed system is developed in MATLAB/SIMULINK.

Keywords

PSO Wind energy system Proportional integral controller 

References

  1. 1.
    Araki, M.: Control Systems, Robotics and Automation—vol II—PID Control. Kyoto University, JapanGoogle Scholar
  2. 2.
    Moradi, M.H., Abedini, M.: Bu Ali Sina University, Hamedan, Iran: A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Electr. Power Energ. Syst. 34, 66–74 (2012)Google Scholar
  3. 3.
    Sahu, R.K., Panda, S., Sekhar, G.T.C.: A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems. Electr. Power Energ. Syst. 64, 880–893 (2015)Google Scholar
  4. 4.
    Rout, U.K., Sahu, R.K., Panda, S.: Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system. Ain Shams Eng. J. 4(3), 409–421 (2013)Google Scholar
  5. 5.
    Kim, D.H., Park J.I.: Intelligent PID controller tuning of AVR system using GA and PSO. ICIC 2005, Part II, LNCS 3645, pp. 366–375. Springer, Berlin (2005)Google Scholar
  6. 6.
    Yoshida, H., Kawata, K., Fukuyana, Y.: A particle swarm optimization for reactive power and voltage control considering voltage stability. In: IEEE International Conference on Intelligent System Applications to Power Systems, April 4–8 (1999)Google Scholar
  7. 7.
    Sivanandam, S.N., Deepa, S.N.: Introduction to Genetic Algorithms. Springer Publications Co. (2010)Google Scholar
  8. 8.
    Somashekar, B., Chandrasekhar, B., Livingston, D.: Modeling and simulation of three to nine phase using special transformer connection. Int. J. Emerg. Technol. Adv. Eng. 3(6) (2013)Google Scholar
  9. 9.
    Hassanpoor, A., Norrga, S., Nee, H., Angquist, L.: Evaluation of different carrier-based PWM methods for modular multilevel converters for HVDC application. In: Proceedings Conference on IEEE Industrial Electronics Society, pp. 388–393 (2012)Google Scholar
  10. 10.
    Chen, Z., Senior Member, IEEE, Guerrero, J.M., Senior Member, IEEE, Blaabjerg, F., Fellow, IEEE: A review of the state of the art of power electronics for wind turbines. IEEE Trans. Power Electron. 24(8) (2009)Google Scholar
  11. 11.
    Solihin, M.I., Tack, L.F., Kean, M.L.: Tuning of PID controller using particle swarm optimization (PSO). In: Proceeding of the International Conference on Advanced Science, Engineering and Information Technology (2011)Google Scholar
  12. 12.
    Malik, S., Dutta, P., Chakrabarti, S., Barman, A.: Parameter estimation of a PID controller using particle swarm optimization Algorithm. Int. J. Adv. Res. Comput. Commun. Eng. 3(3) (2014)Google Scholar
  13. 13.
    Rodriguez, J., Lai, J.S., Peng, F.Z.: Multilevel inverters: a survey of topologies, controls, and applications. IEEE Trans. Ind. Electron. 4(4), 724–738 (2002)CrossRefGoogle Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • L. V. Suresh Kumar
    • 1
    Email author
  • G. V. Nagesh Kumar
    • 2
  • D. Anusha
    • 1
  1. 1.Department of EEEGMR Institute of TechnologyRajamIndia
  2. 2.Department of EEEGITAM UniversityVishakapatnamIndia

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