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Multi Objective Optimization in Charge Management of Micro Grid Based Multistory Carpark

Author

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  • Lukáš Prokop

    (Centre ENET at VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic
    Department of Electric Power Engineering at Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic)

  • Tomáš Vantuch

    (Centre ENET at VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic
    Department of Computer Science at Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic)

  • Stanislav Mišák

    (Centre ENET at VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic
    Department of Electric Power Engineering at Faculty of Electrical Engineering and Computer Science, VŠB-TU Ostrava, 708 00 Ostrava, Czech Republic)

Abstract

Distributed power supply with the use of renewable energy sources and intelligent energy flow management has undoubtedly become one of the pressing trends in modern power engineering, which also inspired researchers from other fields to contribute to the topic. There are several kinds of micro grid platforms, each facing its own challenges and thus making the problem purely multi objective. In this paper, an evolutionary driven algorithm is applied and evaluated on a real platform represented by a private multistory carpark equipped with photovoltaic solar panels and several battery packs. The algorithm works as a core of an adaptive charge management system based on predicted conditions represented by estimated electric load and production in the future hours. The outcome of the paper is a comparison of the optimized and unoptimized charge management on three different battery setups proving that optimization may often outperform a battery setup with larger capacity in several criteria.

Suggested Citation

  • Lukáš Prokop & Tomáš Vantuch & Stanislav Mišák, 2018. "Multi Objective Optimization in Charge Management of Micro Grid Based Multistory Carpark," Energies, MDPI, vol. 11(7), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1791-:d:156867
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    References listed on IDEAS

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    2. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
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