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Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm

Author

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  • Alhassan H. Alattar

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • S. I. Selem

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Hamid M. B. Metwally

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Ahmed Ibrahim

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt
    Department of Electric power systems, School of Energy and Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Raef Aboelsaud

    (Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt
    Department of Electric power systems, School of Energy and Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Mohamed A. Tolba

    (Nuclear Researches Center, Egyptian Atomic Energy Authority (EAEA), Cairo 11787, Egypt
    Electrical Power System Department, Moscow Power Engineering Institute, Moscow 111250, Russia)

  • Ali M. El-Rifaie

    (College of Engineering and Technology, American University of Middle East, Eqaila 15453, Kuwait)

Abstract

Frequency control represents a critically significant issue for the enhancement of the dynamic performance of isolated micro grids. The micro grid system studied here was a wind–diesel system. A new and robust optimization technique called the mine blast algorithm (MBA) was designed for tuning the PID (proportional–integral–differential) gains of the blade pitch controller of the wind turbine side and the gains of the superconducting magnetic energy storage (SMES) controller. SMES was implemented to release and absorb active power quickly in order to achieve a balance between generation and load power, and thereby control system frequency. The minimization of frequency and output wind power deviations were considered as objective functions for the PID controller of the wind turbine, and the diesel frequency and power deviations were used as objective functions for optimizing the SMES controller gains. Different case studies were considered by applying disturbances in input wind, load power, and wind gust, and sensitivity analysis was conducted by applying harsh conditions with varying fluid coupling parameter of the wind–diesel hybrid system. The proposed MBA–SMES was compared with MBA (tuned PID pitch controller) and classical PI control systems in the Matlab environment. Simulation results showed that the MBA–SMES scheme damped the oscillations in the system output responses and improved the system performance by reducing the overshoot by 75% and 36% from classical and MBA-based systems, respectively, reduced the settling time by 45% compared to other systems, and set the final steady-state error of the frequency deviation to zero compared to other systems. The proposed scheme was extremely robust to disturbances and parameter variations.

Suggested Citation

  • Alhassan H. Alattar & S. I. Selem & Hamid M. B. Metwally & Ahmed Ibrahim & Raef Aboelsaud & Mohamed A. Tolba & Ali M. El-Rifaie, 2019. "Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm," Energies, MDPI, vol. 12(16), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3110-:d:257250
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. Sergey Obukhov & Emad M. Ahmed & Denis Y. Davydov & Talal Alharbi & Ahmed Ibrahim & Ziad M. Ali, 2021. "Modeling Wind Speed Based on Fractional Ornstein-Uhlenbeck Process," Energies, MDPI, vol. 14(17), pages 1-15, September.
    4. Abdul Latif & S. M. Suhail Hussain & Dulal Chandra Das & Taha Selim Ustun, 2021. "Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid," Energies, MDPI, vol. 14(9), pages 1-15, April.
    5. Muhammad Majid Gulzar & Muhammad Iqbal & Sulman Shahzad & Hafiz Abdul Muqeet & Muhammad Shahzad & Muhammad Majid Hussain, 2022. "Load Frequency Control (LFC) Strategies in Renewable Energy-Based Hybrid Power Systems: A Review," Energies, MDPI, vol. 15(10), pages 1-23, May.

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