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Optimizing Load Frequency Control in Standalone Marine Microgrids Using Meta-Heuristic Techniques

Author

Listed:
  • Sanath Alahakoon

    (School of Engineering and Technology, Central Queensland University, Rockhampton 4701, Australia)

  • Rajib Baran Roy

    (School of Engineering and Technology, Central Queensland University, Rockhampton 4701, Australia)

  • Shantha Jayasinghe Arachchillage

    (Australian Energy Market Operator, Melbourne 3000, Australia
    Australian Maritime College, University of Tasmania, Launceston 7250, Australia)

Abstract

Integrating renewable resources into the electrical systems of marine vessels achieves the dual goal of diversifying energy resources and reducing greenhouse gas emissions. The presence of intermittent renewable sources and sudden nonlinear load changes can cause frequency deviations in isolated hybrid marine microgrids. To address this issue, the paper proposes a conventional PID (proportional–integral–derivative)-controller-based LFC (load frequency controller) which is optimized by meta-heuristic optimization algorithms, namely, PSO (particle swarm optimization), GWO (grey wolf optimization) and hybrid PSO-GWO. The proposed LFC was designed using transfer functions of various microgrid components, with ITAE (integral time absolute error) and ITSE (integral time square error) serving as performance indices. The proposed LFC’s validation was performed through HIL (hardware-in-loop) real-time simulation using a DS 1104 R&D controller board, with simulation results showing the better performance of the optimized frequency response compared to the nonoptimized LFC controller in terms of rise time, fall time, slew rate and overshoot. The hybrid PSO-GWO algorithm performs better than the other optimization algorithms. The simulation results demonstrate the stability and robustness of the proposed controller. In summary, the proposed PID-controller-based LFC can regulate frequency deviation in standalone hybrid marine microgrids effectively.

Suggested Citation

  • Sanath Alahakoon & Rajib Baran Roy & Shantha Jayasinghe Arachchillage, 2023. "Optimizing Load Frequency Control in Standalone Marine Microgrids Using Meta-Heuristic Techniques," Energies, MDPI, vol. 16(13), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4846-:d:1176114
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    References listed on IDEAS

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    1. Latif, Abdul & Hussain, S. M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2021. "Double stage controller optimization for load frequency stabilization in hybrid wind-ocean wave energy based maritime microgrid system," Applied Energy, Elsevier, vol. 282(PA).
    2. Latif, Abdul & Hussain, S.M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2020. "State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems," Applied Energy, Elsevier, vol. 266(C).
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    4. Maraboina Raju & Munish Kumar Gupta & Neeraj Bhanot & Vishal S. Sharma, 2019. "A hybrid PSO–BFO evolutionary algorithm for optimization of fused deposition modelling process parameters," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2743-2758, October.
    5. Aleksandar Cuculić & Dubravko Vučetić & Rene Prenc & Jasmin Ćelić, 2019. "Analysis of Energy Storage Implementation on Dynamically Positioned Vessels," Energies, MDPI, vol. 12(3), pages 1-19, January.
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    Cited by:

    1. Peddakapu, K. & Mohamed, M.R. & Srinivasarao, P. & Licari, J., 2024. "Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems," Applied Energy, Elsevier, vol. 361(C).
    2. Yinghao Shan & Liqian Ma & Xiangkai Yu, 2023. "Hierarchical Control and Economic Optimization of Microgrids Considering the Randomness of Power Generation and Load Demand," Energies, MDPI, vol. 16(14), pages 1-23, July.

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