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An Intelligent Battery Energy Storage-Based Controller for Power Quality Improvement in Microgrids

Author

Listed:
  • Jaber Alshehri

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

  • Muhammad Khalid

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
    Researcher at K.A.CARE Energy Research & Innovation Center at Dhahran, Dhahran 31261, Saudi Arabia)

  • Ahmed Alzahrani

    (Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia)

Abstract

Modern power systems rely on renewable energy sources and distributed generation systems more than ever before; the combination of those two along with advanced energy storage systems contributed widely to the development of microgrids (MGs). One of the significant technical challenges in MG applications is to improve the power quality of the system subjected to unknown disturbances. Hence innovative control strategies are vital to cope with the problem. In this paper, an innovative online intelligent energy storage-based controller is proposed to improve the power quality of a MG system; in particular, voltage and frequency regulation at steady state conditions are targeted. The MG system under consideration in this paper consists of two distributed generators, a diesel synchronous generator, and a photovoltaic power system integrated with a battery energy storage system. The proposed control approach is based on hybrid differential evolution optimization (DEO) and artificial neural networks (ANNs). The controller parameters have been optimized under several operating conditions. The obtained input and output patterns are consequently used to train the ANNs in order to perform an online tuning for the controller parameters. Finally, the proposed DEO-ANN methodology has been evaluated under random disturbances, and its performance is compared with a benchmark controller.

Suggested Citation

  • Jaber Alshehri & Muhammad Khalid & Ahmed Alzahrani, 2019. "An Intelligent Battery Energy Storage-Based Controller for Power Quality Improvement in Microgrids," Energies, MDPI, vol. 12(11), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2112-:d:236579
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    References listed on IDEAS

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    Cited by:

    1. Ahmed Alzahrani & Hussain Alharthi & Muhammad Khalid, 2019. "Minimization of Power Losses through Optimal Battery Placement in a Distributed Network with High Penetration of Photovoltaics," Energies, MDPI, vol. 13(1), pages 1-16, December.
    2. Marcin Kopiczko & Jaroslaw Jaworski, 2021. "Characteristics of the Parameters of Lithium Iron Phosphate Energy Storage in the Context of their Usefulness in the Management of Distribution Grid," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 817-826.
    3. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of the Control of a Grid Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(7), pages 1-32, March.
    4. Abbas Marini & Luigi Piegari & S-Saeedallah Mortazavi & Mohammad-S Ghazizadeh, 2020. "Coordinated Operation of Energy Storage Systems for Distributed Harmonic Compensation in Microgrids," Energies, MDPI, vol. 13(3), pages 1-22, February.
    5. Felipe J. Zimann & Eduardo V. Stangler & Francisco A. S. Neves & Alessandro L. Batschauer & Marcello Mezaroba, 2020. "Coordinated Control of Active and Reactive Power Compensation for Voltage Regulation with Enhanced Disturbance Rejection Using Repetitive Vector-Control," Energies, MDPI, vol. 13(11), pages 1-18, June.
    6. Marcel Nicola & Claudiu-Ionel Nicola, 2021. "Fractional-Order Control of Grid-Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers," Energies, MDPI, vol. 14(2), pages 1-25, January.
    7. Olga Pilipczuk, 2022. "Cognitive Computing—Will It Be the Future “Smart Power” for the Energy Enterprises?," Energies, MDPI, vol. 15(17), pages 1-19, August.

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