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Fuzzy PID Controller for Automatic Generation Control of Interconnected Power System Tuned by Glow-Worm Swarm Optimization

  • Ramana Pilla
  • Nirupama Botcha
  • Tulasichandra Sekhar GorripotuEmail author
  • Ahmad Taher Azar
Conference paper
  • 56 Downloads
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 5)

Abstract

In this article Fuzzy-Proportional Integral Derivative controller (Fuzzy-PID) is proposed for Automatic Generation Control (AGC) problem of multi area thermal hydropower system. At the outset, a two area hydro thermal power system is developed in the MATLAB/SIMULINK environment. Non-linearities like backlash, transport delay (TD) and generation rate constraint (GRC) are incorporated at the suitable positions in the system and fuzzy-PID controllers are kept as a secondary controller to diminish AGC problem. The superiority of fuzzy-PID controller is explored by comparing with integral, proportional integral (PI) and PID controllers. The controller parameters have been tuned with Glow-worm Swarm Optimization (GSO) algorithm and the Integral Time Absolute Error (ITAE) is used as an objective function. The results are verified through simulations and experiments. The optimized fuzzy-PID controller shows good closed-loop responses in control multi area thermal hydropower system.

Keywords

Automatic Generation Control (AGC) Fuzzy-PID Glow-worm Swarm Optimization (GSO) Integral Time Absolute Error (ITAE) 

References

  1. 1.
    Bevrani H (2009) Robust power system frequency control. Springer, BostonzbMATHCrossRefGoogle Scholar
  2. 2.
    Bervani H, Hiyama T (2011) Intelligent automatic generation control. CRC Press, Boca RatonGoogle Scholar
  3. 3.
    Sahu RK, Panda S, Padhan S (2014) Optimal gravitational search algorithm for automatic generation control of interconnected power systems. Ain Shams Eng J 5(3):721–733CrossRefGoogle Scholar
  4. 4.
    Rakhshani E (2012) Intelligent linear-quadratic optimal output feedback regulator for a deregulated automatic generation control system. Electr Power Compon Syst 40(5):513–533CrossRefGoogle Scholar
  5. 5.
    Singh VP, Mohanty SR, Kishor N, Ray PK (2013) Robust H-infinity load frequency control in hybrid distributed generation system. Int J Electr Power Energy Syst 46:294–305CrossRefGoogle Scholar
  6. 6.
    Azar AT, Serrano FE (2014) Robust IMC-PID tuning for cascade control systems with gain and phase margin specifications. Neural Comput Appl 25(5):983–995CrossRefGoogle Scholar
  7. 7.
    Ali ES, Abd-Elazim SM (2013) BFOA based design of PID controller for two area load frequency control with nonlinearities. Int J Electr Power Energy Syst 51(2013):224–231CrossRefGoogle Scholar
  8. 8.
    Gorripotu TS, Sahu RK, Panda S (2015). Comparative performance analysis of classical controllers in LFC using FA technique. In: IEEE International conference on electrical, electronics, signals, communication and optimization (EESCO), 24–25 January 2015, Visakhapatnam, India.  https://doi.org/10.1109/EESCO.2015.7254014
  9. 9.
    Ammar HH, Azar AT (2020) Robust path tracking of mobile robot using fractional order PID controller. In: Hassanien A, Azar A, Gaber T, Bhatnagar RF, Tolba M (eds.) The International conference on advanced machine learning technologies and applications (AMLTA 2019). AMLTA 2019. Advances in Intelligent Systems and Computing, vol 921. Springer, ChamGoogle Scholar
  10. 10.
    Azar AT, Vaidyanathan S, Ouannas A (2017) Fractional order control and synchronization of chaotic systems. Studies in Computational Intelligence, vol. 688. Springer, Germany. ISBN 978-3-319-50248-9Google Scholar
  11. 11.
    Taher SA, Fini MH, Aliabadi SF (2014) Fractional order PID controller design for LFC in electric power systems using imperialist competitive Algorithm. Ain Shams Eng J 5(1):121–135CrossRefGoogle Scholar
  12. 12.
    Ghoudelbourk S, Dib D, Omeiri A, Azar AT (2016) MPPT Control in wind energy conversion systems and the application of fractional control (PIα) in pitch wind turbine. Int. J. Model Ident Control (IJMIC) 26(2):140–151CrossRefGoogle Scholar
  13. 13.
    Gorripotu TS, Samalla H, Jagan Mohana Rao C, Azar AT, Pelusi D (2019) TLBO algorithm optimized fractional-order PID controller for AGC of interconnected power system. In: Nayak J, Abraham A, Krishna B, Chandra Sekhar G, Das A (eds.) Soft computing in data analytics. Advances in Intelligent Systems and Computing, vol 758. Springer, SingaporeGoogle Scholar
  14. 14.
    Azar AT, Serrano FE (2019) Fractional order two degree of freedom PID controller for a robotic manipulator with a fuzzy Type-2 compensator. In: Hassanien A, Tolba M, Shaalan K, Azar A (eds.) Proceedings of the international conference on advanced intelligent systems and informatics 2018, AISI 2018. Advances in Intelligent Systems and Computing, vol 845. Springer, ChamGoogle Scholar
  15. 15.
    Azar AT, Serrano FE (2018) Fractional order sliding mode PID controller/observer for continuous nonlinear switched systems with PSO parameter tuning. In: Hassanien A, Tolba M, Elhoseny M, Mostafa M (eds.) The International conference on advanced machine learning technologies and applications (AMLTA 2018). Advances in Intelligent Systems and Computing, vol 723, pp 13–22. Springer, ChamCrossRefGoogle Scholar
  16. 16.
    Dash P, Saikia LC, Sinha N (2015) Automatic generation control of multi area thermal system using bat algorithm optimized PD–PID cascade controller. Int J Electr Power Energy Syst 68(2015):364–372CrossRefGoogle Scholar
  17. 17.
    Prakash S, Sinha SK (2014) Simulation based neuro-fuzzy hybrid intelligent PI control approach in four-area load frequency control of interconnected power system. Appl Soft Comput 23(2014):152–164CrossRefGoogle Scholar
  18. 18.
    Nayak JR, Shaw B, Sahu BK (2018) Application of adaptive-SOS (ASOS) algorithm based interval type-2 fuzzy-PID controller with derivative filter for automatic generation control of an interconnected power system. Eng Sci Technol Int J 21(3):465–485CrossRefGoogle Scholar
  19. 19.
    Gorripotu TS, Sahu RK, Baliarsingh AK, Panda S (2016) Load frequency control of power system under deregulated environment using optimal firefly algorithm. Int J Electr Power Energy Syst 74(2016):195–211Google Scholar
  20. 20.
    Sahu RK, Panda S, Gorripotu TS (2015) A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems. Int J Electr Power Energy Syst 64:880–893CrossRefGoogle Scholar
  21. 21.
    Eberhart R, Shi Y, Kennedy J (2001) Swarm intelligence. ElsevierGoogle Scholar
  22. 22.
    Saikia LC, Sinha N (2016) Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller. Int J Electr Power Energy Syst 80(2016):52–63Google Scholar
  23. 23.
    Yang XS (2010) A new metaheuristic bat-inspired algorithm. In: González JR, Pelta DA, Cruz C, Terrazas G, Krasnogor N (eds.) Nature inspired cooperative strategies for optimization (NICSO 2010). Studies in Computational Intelligence, vol 284. Springer, HeidelbergGoogle Scholar
  24. 24.
    Yang XS, Deb S (2014) Cuckoo search: recent advances and applications. Neural Comput Appl 24(1):169–174CrossRefGoogle Scholar
  25. 25.
    Abdelaziz AY, Ali ES (2015) Cuckoo search algorithm based load frequency controller design for nonlinear interconnected power system. Int J Electr Power Energy Syst 73(2015):632–643CrossRefGoogle Scholar
  26. 26.
    Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of ICNN 1995 - International conference on neural networks, vol 4, pp 1942–1948Google Scholar
  27. 27.
    Mohanty B, Hota PK (2018) A hybrid chemical reaction-particle swarm optimisation technique for automatic generation control. J Electr Syst Inf Technol 5(2):229–244Google Scholar
  28. 28.
    Krishnanand KN, Ghose D (2015) Detection of multiple source locations using a glowworm metaphor with applications to collective robotics. In: 2005 Proceedings 2005 IEEE Swarm Intelligence Symposium, SIS 2005, 8–10 June 2005, Pasadena, CA, USA, pp 84–91.  https://doi.org/10.1109/sis.2005.1501606

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Ramana Pilla
    • 1
  • Nirupama Botcha
    • 2
  • Tulasichandra Sekhar Gorripotu
    • 2
    Email author
  • Ahmad Taher Azar
    • 3
    • 4
  1. 1.Department of Electrical and Electronics EngineeringGMR Institute of TechnologySrikakulamIndia
  2. 2.Department of Electrical and Electronics EngineeringSri Sivani College of EngineeringSrikakulamIndia
  3. 3.College of EngineeringPrince Sultan UniversityRiyadhKingdom of Saudi Arabia
  4. 4.Faculty of Computers and Artificial IntelligenceBenha UniversityBenhaEgypt

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