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Load Frequency Control Based on Evolutionary Techniques in Electrical Power Systems

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Advances in Chaos Theory and Intelligent Control

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 337))

Abstract

Load Frequency Control (LFC) used to regulate the power output of the electric generator within an area as the response of changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. The disadvantage of this type of controllers that there are slow and does not allow the controller designer to take into account possible changes in operating conditions and non- linearities in the generator unit. Moreover, it lacks robustness. So there are many modern techniques used to tune the controller. This chapter discusses the application of evolutionary techniques in Load Frequency Control (LFC) in power systems. It gives introduction to evolutionary techniques. Then it presents the problem formulation for load frequency control with Evolutionary Particle Swarm Optimization (MAACPSO). It gives the application of Particle Swarm Optimization (PSO) in load frequency control, also it illustrates the use of a Adaptive Weight Particle Swarm Optimization (AWPSO), Adaptive Accelerated Coefficients based PSO, (AACPSO) Adaptive Accelerated Coefficients based PSO (AACPSO). Furthermore, it introduces a new modification for AACPSO technique (MAACPSO). The new technique will be explained inside the chapter, it is abbreviated to Modified Adaptive Accelerated Coefficients based PSO (MAACPSO). A well done comparison will be given in this chapter for these above mentioned techniques. A reasonable discussion on the obtained results will be displayed. The obtained results are promising.

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Author information

Authors and Affiliations

  1. Electrical Communication Department, Faculty of Engineering, Canadian International College (CIC), 6 October City, Giza, Egypt

    Naglaa K. Bahgaat

  2. Electrical Power Engineering Department Faculty of Engineering, Al-Azhar University, Cairo, Egypt

    M. I. El-Sayed

  3. Electrical Power Engineering Department Faculty of Engineering, Cairo University, Giza, Egypt

    M. A. Moustafa Hassan

  4. Electrical Power Engineering Department Faculty of Engineering, Banha University, Cairo, Egypt

    F. Bendary

Authors
  1. Naglaa K. Bahgaat
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  2. M. I. El-Sayed
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  3. M. A. Moustafa Hassan
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  4. F. Bendary
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Corresponding author

Correspondence to Naglaa K. Bahgaat .

Editor information

Editors and Affiliations

  1. Benha University, Benha, Egypt

    Ahmad Taher Azar

  2. Chennai, India

    Sundarapandian Vaidyanathan

Appendix

Appendix

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Bahgaat, N.K., El-Sayed, M.I., Moustafa Hassan, M.A., Bendary, F. (2016). Load Frequency Control Based on Evolutionary Techniques in Electrical Power Systems. In: Azar, A., Vaidyanathan, S. (eds) Advances in Chaos Theory and Intelligent Control. Studies in Fuzziness and Soft Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-30340-6_36

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  • DOI: https://doi.org/10.1007/978-3-319-30340-6_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30338-3

  • Online ISBN: 978-3-319-30340-6

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