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  • Volume 2018

    Intelligent Control Algorithm for Distributed Battery Energy Storage Systems
    (International Journal of Engineering Works)

    Vol. 5, Issue 12, PP. 252-259, December 2018
    DOI
    Keywords: Battery energy storage systems, State of charge, Control algorithm, Renewable energy

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    Abstract

    Recent trends towards bulk renewable energy penetration in the power grid have made it essential to have reserve power in the system to overcome variability and intermittent nature of renewable energy sources. Battery energy storage systems (BESS) are vastly utilized for this purpose but the cost and limited life of batteries limits its use. In this paper a control strategy for battery energy storage systems is proposed in which batteries are discharged based on state of charge and state of health. Simulations are performed in MATLAB. By implementing this algorithm load can be shifted small batteries to batteries with better health and capacity. The results show the working of algorithm and the selection of batteries based on set input variable. In this way battery energy storage systems will have longer lifetime, better efficiency and economical operation. 

    Author

    1. Asfand Yar Ali: US Pakistan center for Advance Studies in energy, University of Engineering and Technology Peshawar
    2. Juveria Anwar: US Pakistan center for Advance Studies in energy, University of Engineering and Technology Peshawar
    3. Rabia bibi: US Pakistan center for Advance Studies in energy, University of Engineering and Technology Peshawar
    4. Muhammad Raheel Khattak: US Pakistan center for Advance Studies in energy, University of Engineering and Technology Peshawar
    5. Abdul Basit: US Pakistan center for Advance Studies in energy, University of Engineering and Technology Peshawar

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    Cite

    Asfand Yar Ali Juveria Anwar Rabia bibi Muhammad Raheel Khattak and Abdul Basit, Intelligent Control Algorithm for Distributed Battery Energy Storage Systems, International Journal of Engineering Works, Vol. 5 Issue 12 PP. 252-259 December 2018

    References

    [1] Trenberth, K., et al., Observations: surface and atmospheric climate change. Chapter 3. Climate change, 2007: p. 235-336.
    [2] Cline, W.R., The economics of global warming. 1992: Institute for International Economics.
    [3] Rogelj, J., et al., Paris Agreement climate proposals need a boost to keep warming well below 2 C. Nature, 2016. 534(7609): p. 631.
    [4] Pittock, A.B., Climate change: turning up the heat. 2017: Routledge.
    [5] Painuly, J.P., Barriers to renewable energy penetration; a framework for analysis. Renewable energy, 2001. 24(1): p. 73-89.
    [6] Singh, M., et al., Grid interconnection of renewable energy sources at the distribution level with power-quality improvement features. IEEE transactions on power delivery, 2011. 26(1): p. 307-315.
    [7] Divya, K. and J. Østergaard, Battery energy storage technology for power systems—An overview. Electric power systems research, 2009. 79(4): p. 511-520.
    [8] Oudalov, A., R. Cherkaoui, and A. Beguin. Sizing and optimal operation of battery energy storage system for peak shaving application. in Power Tech, 2007 IEEE Lausanne. 2007. IEEE.
    [9] Nykvist, B. and M. Nilsson, Rapidly falling costs of battery packs for electric vehicles. nature climate change, 2015. 5(4): p. 329.
    [10] Vrettos, E.I. and S.A. Papathanassiou, Operating policy and optimal sizing of a high penetration RES-BESS system for small isolated grids. IEEE Transactions on Energy Conversion, 2011. 26(3): p. 744-756.
    [11] Ning, G., B. Haran, and B.N. Popov, Capacity fade study of lithium-ion batteries cycled at high discharge rates. Journal of Power Sources, 2003. 117(1-2): p. 160-169.