Skip to main content

Use of Fuzzy-Enabled FOPID Controller for AGC Investigation Utilizing Squirrel Search Algorithm

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1005))

Abstract

This article presents an innovative fuzzy-enabled fractional order proportional-integral-derivative (Fuzzy-FOPID) controller for automatic generation control (AGC) of a dual control area amalgamated power framework. Because of the convergence superiority, the parameters for the fuzzy-FOPID controllers are calibrated with the newly developed optimization strategy termed as squirrel search algorithm (SSA). A disturbance having an extent of 0.01 p.u. is applied to control area-1 to check the performance of the proposed system. Toward the finish of the investigation, the implementation of the fuzzy-FOPID controller was contrasted against fuzzy-enabled PID, traditional PID controllers regarding peak and least overshoots, settling time, relaxing time and steady-state error. The efficiency of the projected SSA tuned fuzzy-FOPID controller has been evidenced by intensifying the loading of the system.

This is a preview of subscription content, log in via an institution.

References

  1. Kundur, P., Balu, N.J., Lauby, M.G.: Power System Stability and Control, vol. 7. McGraw-Hill, New York (1994)

    Google Scholar 

  2. Elgerd, O.I., Fosha, C.E.: Optimum megawatt-frequency control of multiarea electric energy systems. IEEE Trans. Power Apparatus Syst. 4, 556–563 (1970)

    Article  Google Scholar 

  3. Kumar, A., Malik, O.P.: Automatic generation control of interconnected power systems using variable-structure controllers. In: IEE Proceedings C-Generation, Transmission and Distribution, vol. 130, no. 4. IET (1983)

    Google Scholar 

  4. Bakken, B.H., Grande, O.S.: Automatic generation control in a deregulated power system. IEEE Trans. Power Syst. 13(4), 1401–1406 (1998)

    Article  Google Scholar 

  5. Fosha, C.E., Elgerd, O.I.: The megawatt-frequency control problem: a new approach via optimal control theory. IEEE Trans. Power Apparatus Syst. 4, 563–577 (1970)

    Article  Google Scholar 

  6. Demiroren, A., Sengor, N.S., Lale Zeynelgil, H.: Automatic generation control by using ANN technique. Electr. Power Compon. Syst. 29(10) (2001): 883–896

    Google Scholar 

  7. Chown, G.A., Hartman, R.C.: Design and experience with a fuzzy logic controller for automatic generation control (AGC). IEEE Trans. Power Syst. 13(3), 965–970 (1998)

    Article  Google Scholar 

  8. Nanda, J., Mangla, A.: Automatic generation control of an interconnected hydro-thermal system using conventional integral and fuzzy logic controller. In: Proceedings of the 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, 2004 (DRPT 2004), vol. 1. IEEE (2004)

    Google Scholar 

  9. Shayeghi, H., Shayanfar, H.A., Jalili, A.: Load frequency control strategies: a state-of-the-art survey for the researcher. Energy Convers. Manag. 50(2), 344–353 (2009)

    Article  Google Scholar 

  10. Sudha, K.R., Vijaya Santhi, R.: Load frequency control of an interconnected reheat thermal system using type-2 fuzzy system including SMES units. Int. J. Electr. Power Energy Syst. 43(1), 1383–1392 (2012)

    Article  Google Scholar 

  11. Nanda, J., Mangla, A., Suri, S.: Some new findings on automatic generation control of an interconnected hydrothermal system with conventional controllers. IEEE Trans. Energy Convers. 21(1), 187–194 (2006)

    Article  Google Scholar 

  12. Gozde, H., Cengiz Taplamacioglu, M., Kocaarslan, I.: Comparative performance analysis of artificial bee colony algorithm in automatic generation control for interconnected reheat thermal power system. Int. J. Electr. Power Energy Syst. 42(1), 167–178 (2012)

    Article  Google Scholar 

  13. Sahu, B.K., Pati, S., Panda, S.: Hybrid differential evolution particle swarm optimisation optimised fuzzy proportional–integral derivative controller for automatic generation control of interconnected power system. IET Gener. Transm. Distrib. 8(11), 1789–1800 (2014)

    Article  Google Scholar 

  14. Debnath, M.K., Mallick, R.K., Sahu, B.K.: Application of hybrid differential evolution–Grey Wolf optimization algorithm for automatic generation control of a multi-source interconnected power system using optimal fuzzy–PID controller. Electr. Power Compon. Syst. 45(19), 2104–2117 (2017)

    Article  Google Scholar 

  15. Jain, M., Singh, V., Rani, A.: A novel nature-inspired algorithm for optimization: squirrel search algorithm. Swarm Evol. Comput. (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Manoj Kumar Debnath .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Singh, M.B., Pal, S., Mohanty, S., Debnath, M.K. (2020). Use of Fuzzy-Enabled FOPID Controller for AGC Investigation Utilizing Squirrel Search Algorithm. In: Patnaik, S., Ip, A., Tavana, M., Jain, V. (eds) New Paradigm in Decision Science and Management. Advances in Intelligent Systems and Computing, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-9330-3_35

Download citation

Publish with us

Policies and ethics