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Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system

Author

Listed:
  • Shafaat Ullah
  • Laiq Khan
  • Rabiah Badar
  • Ameen Ullah
  • Fazal Wahab Karam
  • Zain Ahmad Khan
  • Atiq Ur Rehman

Abstract

The state-of-charge (SoC) of an energy storage system (ESS) should be kept in a certain safe range for ensuring its state-of-health (SoH) as well as higher efficiency. This procedure maximizes the power capacity of the ESSs all the times. Furthermore, economic load dispatch (ELD) is implemented to allocate power among various ESSs, with the aim of fully meeting the load demand and reducing the total operating cost. In this research article, a distributed multi-agent consensus based control algorithm is proposed for multiple battery energy storage systems (BESSs), operating in a microgrid (MG), for fulfilling several objectives, including: SoC trajectories tracking control, economic load dispatch, active and reactive power sharing control, and voltage and frequency regulation (using the leader-follower consensus approach). The proposed algorithm considers the hierarchical control structure of the BESSs and the frequency/voltage droop controllers with limited information exchange among the BESSs. It embodies both self and communication time-delays, and achieves its objectives along with offering plug-and-play capability and robustness against communication link failure. Matlab/Simulink platform is used to test and validate the performance of the proposed algorithm under load disturbances through extensive simulations carried out on a modified IEEE 57-bus system. A detailed comparative analysis of the proposed distributed control strategy is carried out with the distributed PI-based conventional control strategy for demonstrating its superior performance.

Suggested Citation

  • Shafaat Ullah & Laiq Khan & Rabiah Badar & Ameen Ullah & Fazal Wahab Karam & Zain Ahmad Khan & Atiq Ur Rehman, 2020. "Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-44, May.
    • Handle: RePEc:plo:pone00:0232638
    DOI: 10.1371/journal.pone.0232638
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    References listed on IDEAS

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    1. Tung-Lam Nguyen & Efren Guillo-Sansano & Mazheruddin H. Syed & Van-Hoa Nguyen & Steven M. Blair & Luis Reguera & Quoc-Tuan Tran & Raphael Caire & Graeme M. Burt & Catalin Gavriluta & Ngoc-An Luu, 2018. "Multi-Agent System with Plug and Play Feature for Distributed Secondary Control in Microgrid—Controller and Power Hardware-in-the-Loop Implementation," Energies, MDPI, vol. 11(12), pages 1-21, November.
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    Cited by:

    1. Zhengxin, Jiang & Qin, Shi & Yujiang, Wei & Hanlin, Wei & Bingzhao, Gao & Lin, He, 2021. "An Immune Genetic Extended Kalman Particle Filter approach on state of charge estimation for lithium-ion battery," Energy, Elsevier, vol. 230(C).
    2. Shafaat Ullah & Laiq Khan & Irfan Sami & Ghulam Hafeez & Fahad R. Albogamy, 2021. "A Distributed Hierarchical Control Framework for Economic Dispatch and Frequency Regulation of Autonomous AC Microgrids," Energies, MDPI, vol. 14(24), pages 1-23, December.
    3. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
    4. Shafaat Ullah & Laiq Khan & Mohsin Jamil & Muhammad Jafar & Sidra Mumtaz & Saghir Ahmad, 2021. "A Finite-Time Robust Distributed Cooperative Secondary Control Protocol for Droop-Based Islanded AC Microgrids," Energies, MDPI, vol. 14(10), pages 1-26, May.
    5. Wonpoong Lee & Myeongseok Chae & Dongjun Won, 2022. "Optimal Scheduling of Energy Storage System Considering Life-Cycle Degradation Cost Using Reinforcement Learning," Energies, MDPI, vol. 15(8), pages 1-19, April.
    6. Ritu Kandari & Neeraj Neeraj & Alexander Micallef, 2022. "Review on Recent Strategies for Integrating Energy Storage Systems in Microgrids," Energies, MDPI, vol. 16(1), pages 1-24, December.

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