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Frequency Stabilization in an Interconnected Micro-Grid Using Smell Agent Optimization Algorithm-Tuned Classical Controllers Considering Electric Vehicles and Wind Turbines

Author

Listed:
  • Shreya Vishnoi

    (Maulana Azad National Institute of Technology Bhopal, Bhopal 462003, India)

  • Srete Nikolovski

    (Power Engineering Department, Faculty of Electrical Engineering, Computer Science and Information Technology, J. J. Strossmayer University of Osijek, K. Trpimira 2B, HR-31000 Osijek, Croatia)

  • More Raju

    (Maulana Azad National Institute of Technology Bhopal, Bhopal 462003, India)

  • Mukesh Kumar Kirar

    (Maulana Azad National Institute of Technology Bhopal, Bhopal 462003, India)

  • Ankur Singh Rana

    (Department of Electrical and Electronics Engineering, National Institute of Technology Tiruchirappalli, Tiruchirappalli 620015, India)

  • Pawan Kumar

    (Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala 147004, India)

Abstract

In micro-grids (MGs), renewable energy resources (RESs) supply a major portion of the consumer demand. The intermittent nature of these RESs and the stochastic characteristics of the loads cause a frequency stabilization issue in MGs. Owing to this, in the present manuscript, the authors try to uncover the frequency stabilization/regulation issue (FRI) in a two-area MG system comprising wind turbines (WTs), an aqua-electrolyzer, a fuel cell, a bio-gas plant, a bio-diesel plant, diesel generation (DG), ship DG, electric vehicles and their energy storage devices, flywheels, and batteries in each control area. With these sources, the assessment of the FRI is carried out using different classical controllers, namely, the integral (I), proportional plus I (PI), and PI plus derivative (PID) controllers. The gain values of these I, PI, and PID controllers are tuned using the recently proposed smell agent optimization (SAO) algorithm. The simulation studies reveal the outstanding performance of the later controller compared with the former ones in view of the minimum settling period and peak amplitude deviations (overshoots and undershoots). The SAO algorithm shows superior convergence behavior when tested against particle swarm optimization and the firefly algorithm. The SAO-PID controller effectively performs in continuously changing and increased demand situations. The SAO-PID controller designed in nominal conditions was found to be insensitive to wide deviations in load demands and WT time constants.

Suggested Citation

  • Shreya Vishnoi & Srete Nikolovski & More Raju & Mukesh Kumar Kirar & Ankur Singh Rana & Pawan Kumar, 2023. "Frequency Stabilization in an Interconnected Micro-Grid Using Smell Agent Optimization Algorithm-Tuned Classical Controllers Considering Electric Vehicles and Wind Turbines," Energies, MDPI, vol. 16(6), pages 1-25, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2913-:d:1103986
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    References listed on IDEAS

    as
    1. Soroush Oshnoei & Mohammadreza Aghamohammadi & Siavash Oshnoei & Arman Oshnoei & Behnam Mohammadi-Ivatloo, 2021. "Provision of Frequency Stability of an Islanded Microgrid Using a Novel Virtual Inertia Control and a Fractional Order Cascade Controller," Energies, MDPI, vol. 14(14), pages 1-24, July.
    2. Hiramani Shukla & Srete Nikolovski & More Raju & Ankur Singh Rana & Pawan Kumar, 2022. "A Particle Swarm Optimization Technique Tuned TID Controller for Frequency and Voltage Regulation with Penetration of Electric Vehicles and Distributed Generations," Energies, MDPI, vol. 15(21), pages 1-32, November.
    3. Abdul Latif & Arup Pramanik & Dulal Chandra Das & Israfil Hussain & Sudhanshu Ranjan, 2018. "Plug in hybrid vehicle-wind-diesel autonomous hybrid power system: frequency control using FA and CSA optimized controller," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(5), pages 1147-1158, October.
    4. Sudhanshu Ranjan & D. C. Das & A. Latif & N. Sinha, 2021. "Electric vehicles to renewable-three unequal areas-hybrid microgrid to contain system frequency using mine blast algorithm based control strategy," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(5), pages 961-975, October.
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