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Fuzzy Logic-Based Load Frequency Control in an Island Hybrid Power System Model Using Artificial Bee Colony Optimization

Author

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  • Neelamsetti Kirn Kumar

    (Department of Electrical and Electronics Engineering, M S RAMAIAH Institute of Technology, Bangalore, Karnataka 560054, India)

  • Rahul Sanmugam Gopi

    (Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India)

  • Ramya Kuppusamy

    (Department of Electrical and Electronics Engineering, Sri Sairam College of Engineering, Bangalore 562106, India)

  • Srete Nikolovski

    (Power Engineering Department, Faculty of Electrical Engineering, Computer Science and Information Technology, University of Osijek, 31000 Osijek, Croatia)

  • Yuvaraja Teekaraman

    (Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield S1 3JD, UK)

  • Indragandhi Vairavasundaram

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, India)

  • Siripireddy Venkateswarulu

    (Department of Electrical and Electronics Engineering, Mother Theresa Institute of Engineering and Technology, Palamaner, Andhra Pradesh 517408, India)

Abstract

This study presents the implementation of Artificial Bee Colony (ABC) optimization in an island hybrid power system model using fuzzy logic-based load frequency control. The Island Hybrid Power System considered in this study consisted of various generation units and an energy storage system. The optimized control parameters of PID using ABC were used in an intelligent fuzzy logic controller. The profiles (power & Frequency) of isolated hybrid power system were improved using a Super Conducting Magnetic Energy Storage (SMES) System. Individual controllers were used for wind turbine and diesel generators to control the power output for balancing the demand (frequency change control). Comparative analysis of power and frequency with the help of various classical and intelligent control configurations is presented. The outcome of the study shows that a minimum deviation in frequency and power is obtained through the proposed Intelligent Fuzzy Control approach for the considered isolated power system model.

Suggested Citation

  • Neelamsetti Kirn Kumar & Rahul Sanmugam Gopi & Ramya Kuppusamy & Srete Nikolovski & Yuvaraja Teekaraman & Indragandhi Vairavasundaram & Siripireddy Venkateswarulu, 2022. "Fuzzy Logic-Based Load Frequency Control in an Island Hybrid Power System Model Using Artificial Bee Colony Optimization," Energies, MDPI, vol. 15(6), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2199-:d:773370
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    References listed on IDEAS

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    4. Al-Bahrani, Loau Tawfak & Horan, Ben & Seyedmahmoudian, Mehdi & Stojcevski, Alex, 2020. "Dynamic economic emission dispatch with load dema nd management for the load demand of electric vehicles during crest shaving and valley filling in smart cities environment," Energy, Elsevier, vol. 195(C).
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    Cited by:

    1. Yuanyuan Wang & Zexu Yu & Zhenhai Dou & Mengmeng Qiao & Ye Zhao & Ruishuo Xie & Lianxin Liu, 2022. "Decentralized Coordination Dispatch Model Based on Chaotic Mutation Harris Hawks Optimization Algorithm," Energies, MDPI, vol. 15(10), pages 1-26, May.
    2. Takele Ferede Agajie & Armand Fopah-Lele & Ahmed Ali & Isaac Amoussou & Baseem Khan & Mahmoud Elsisi & Om Prakash Mahela & Roberto Marcelo Álvarez & Emmanuel Tanyi, 2023. "Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant," Sustainability, MDPI, vol. 15(7), pages 1-26, March.

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