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Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS

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Advances in Engineering Research and Application (ICERA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 366))

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Abstract

Managing procedure for charging and discharging battery system plays an essential contributor in improving the performance of energy storage system for example increment of utilizing batteries. This paper aims to develop a new hybrid genetic algorithm-based proportional integral (GA-based PI) controller with an adaptive neuro-fuzzy inference system (ANFIS) for the charging balance of batteries. The dataset is generated by using the GA-based PI controller, then a training strategy is introduced for the ANFIS controller. The proposed approach is evaluated by the GA-based PI controller and the PI controller based on Ziegler Nichols method.

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Acknowledgment

The authors would like to thank Thai Nguyen University of Technology for supporting this research.

Author information

Authors and Affiliations

  1. Industry 4.0 Implementation Center, National Taiwan University of Science and Technology, Taipei, 106, Taiwan

    M. Elsisi & Minh-Quang Tran

  2. Department of Electrical Engineering, Faculty of Engineering (Shoubra), Benha University, 108 Shoubra Street, B.O. Box 11241, Cairo, Egypt

    M. Elsisi

  3. Department of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Minh-Quang Tran & Nguyen Thi Thanh Nga

  4. Falculty of Mechanical Engineering and Mechatronics, PHENIKAA University, Hanoi, 12116, Vietnam

    Vu Thi Lien

Authors
  1. M. Elsisi
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  2. Minh-Quang Tran
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  3. Vu Thi Lien
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  4. Nguyen Thi Thanh Nga
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Corresponding author

Correspondence to Nguyen Thi Thanh Nga .

Editor information

Editors and Affiliations

  1. Faculty of Electronic Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Duy Cuong Nguyen

  2. Faculty of Mechanical Engineering, Thai Nguyen University of Technology, Thai Nguyen, Vietnam

    Ngoc Pi Vu

  3. Vietnam Association for Science Editing, Hanoi University of Science and Technology, Hanoi, Vietnam

    Banh Tien Long

  4. Institute for Automation and Systems Engineering, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Horst Puta

  5. Department of Computer Science and Automation, Ilmenau University of Technology (IUT), Ilmenau, Germany

    Kai-Uwe Sattler

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Elsisi, M., Tran, MQ., Lien, V.T., Nga, N.T.T. (2022). Adaptive Energy Management in Microgrid Based on New Training Strategy for ANFIS. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2021. Lecture Notes in Networks and Systems, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-030-92574-1_15

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  • DOI: https://doi.org/10.1007/978-3-030-92574-1_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92573-4

  • Online ISBN: 978-3-030-92574-1

  • eBook Packages: EngineeringEngineering (R0)

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