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Design and Application of Controller Based on Sine-Cosine Algorithm for Load Frequency Control of Power System

  • Saswati Mishra
  • Shubhrata Gupta
  • Anamika YadavEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 941)

Abstract

Load frequency control (LFC) has emerged as one of the potential research areas in the field of power system. LFC is a mechanism by which the system frequency is maintained within allowable limits by maintaining equilibrium between generation and load. In this study, design and application of controller based on sine-cosine algorithm (SCA) is utilized for LFC of interconnected power system. A proportional-integral-derivative (PID) controller with a filter consisting of derivative term is used and its parameters are tuned using SCA. The performance criterion chosen for tuning process is the minimization of integral error of variations in frequency and tie-line power. To examine the efficacy of SCA-PIDN controller, its performance is compared with other controllers reported in literature. Further, time-domain simulations are illustrated to support the obtained results. Additionally, the robustness of SCA-PIDN controller is examined with random load perturbations. The outcomes of the test cases reveal the superiority of SCA-PIDN controllers over others.

Keywords

Area control error Integral error Load frequency control PID controller Sine-cosine algorithm 

References

  1. 1.
    Wood, A.J., Wollenberg, B.F.: Power Generation, Operation, and Control. Wiley, Hoboken (2012)Google Scholar
  2. 2.
    Kundur, P., Balu, N.J., Lauby, M.G.: Power System Stability and Control. McGraw-Hill, New York (1994)Google Scholar
  3. 3.
    Shayeghi, H., Shayanfar, H., Jalili, A.: Load frequency control strategies: a state-of-the-art survey for the researcher. Energy Convers. Manag. 50(2), 344–353 (2009)CrossRefGoogle Scholar
  4. 4.
    Çam, E., Kocaarslan, I.: Load frequency control in two area power systems using fuzzy logic controller. Energy Convers. Manag. 46(2), 233–243 (2005)CrossRefGoogle Scholar
  5. 5.
    Khuntia, S.R., Panda, S.: Simulation study for automatic generation control of a multi-area power system by ANFIS approach. Appl. Soft Comput. 12(1), 333–341 (2012)CrossRefGoogle Scholar
  6. 6.
    Singh, S.P., Prakash, T., Singh, V., Babu, M.G.: Analytic hierarchy process based automatic generation control of multi-area interconnected power system using Jaya algorithm. Eng. Appl. Artif. Intell. 60, 35–44 (2017)CrossRefGoogle Scholar
  7. 7.
    Mallesham, G., Mishra, S., Jha, A.: Ziegler-Nichols based controller parameters tuning for load frequency control in a microgrid. In: 2011 International Conference on Energy, Automation, and Signal (ICEAS), pp. 1–8. IEEE (2011)Google Scholar
  8. 8.
    Abdel-Magid, Y., Dawoud, M.: Genetic algorithms applications in load frequency control (1995)Google Scholar
  9. 9.
    Ghoshal, S.P.: Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control. Electr. Power Syst. Res. 72(3), 203–212 (2004)CrossRefGoogle Scholar
  10. 10.
    Guha, D., Roy, P.K., Banerjee, S.: Load frequency control of interconnected power system using grey wolf optimization. Swarm Evol. Comput. 27, 97–115 (2016)CrossRefGoogle Scholar
  11. 11.
    Abdelaziz, A., Ali, E.: Cuckoo search algorithm based load frequency controller design for nonlinear interconnected power system. Int. J. Electr. Power Energy Syst. 73, 632–643 (2015)CrossRefGoogle Scholar
  12. 12.
    Barisal, A.: Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems. Int. J. Electr. Power Energy Syst. 66, 67–77 (2015)CrossRefGoogle Scholar
  13. 13.
    Raju, M., Saikia, L.C., Sinha, N.: 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, 52–63 (2016)CrossRefGoogle Scholar
  14. 14.
    Abd-Elazim, S., Ali, E.: Load frequency controller design via BAT algorithm for nonlinear interconnected power system. Int. J. Electr. Power Energy Syst. 77, 166–177 (2016)CrossRefGoogle Scholar
  15. 15.
    Ali, E., Abd-Elazim, S.: Bacteria foraging optimization algorithm based load frequency controller for interconnected power system. Int. J. Electr. Power Energy Syst. 33(3), 633–638 (2011)CrossRefGoogle Scholar
  16. 16.
    Panda, S., Yegireddy, N.K.: Automatic generation control of multi-area power system using multi-objective non-dominated sorting genetic algorithm-II. Int. J. Electr. Power Energy Syst. 53, 54–63 (2013)CrossRefGoogle Scholar
  17. 17.
    Mohanty, B., Panda, S., Hota, P.: Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system. Int. J. Electr. Power Energy Syst. 54, 77–85 (2014)CrossRefGoogle Scholar
  18. 18.
    Jagatheesan, K., et al.: Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity. Neural Comput. Appl. 28(1), 475–488 (2017)CrossRefGoogle Scholar
  19. 19.
    Simhadri, K.S., Mohanty, B., Panda, S.K.: Comparative performance analysis of 2DOF state feedback controller for automatic generation control using whale optimization algorithm. Optim. Control. Appl. MethodsGoogle Scholar
  20. 20.
    Guha, D., Roy, P., Banerjee, S.: A maiden application of salp swarm algorithm optimized cascade tilt-integral-derivative controller for load frequency control of power systems. IET Gener. Transm. Distrib. (2018)Google Scholar
  21. 21.
    Mirjalili, S.: SCA: a sine cosine algorithm for solving optimization problems. Knowl.-Based Syst. 96, 120–133 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Saswati Mishra
    • 1
  • Shubhrata Gupta
    • 1
  • Anamika Yadav
    • 1
    Email author
  1. 1.Department of Electrical EngineeringNational Institute of Technology RaipurRaipurIndia

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