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Design of Battery Storage System for Malaysia Low Voltage Distribution Network with the Presence of Residential Solar Photovoltaic System

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  • Meysam Shamshiri

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia)

  • Chin Kim Gan

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia)

  • Junainah Sardi

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia)

  • Mau Teng Au

    (UNITEN R&D, Kajang 43000, Selangor, Malaysia)

  • Wei Hown Tee

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia)

Abstract

The recent proliferation of residential solar photovoltaic systems has prompted several technical challenges to the operation of low voltage (LV) distribution networks. More specifically, the mismatch of the solar generation and demand profiles, particularly during the midday when the demand is low and solar generation is high, can lead to network overvoltages and increased network losses. In addition, the solar photovoltaic system is not able to reduce the system’s maximum demand, given the residential LV network would normally have an evening peak when the sun goes down. In this regard, this paper examines two different control strategies in designing the battery energy storage system. One aims to eliminate reverse flow caused by the surplus solar energy and the other aims for peak demand reduction.

Suggested Citation

  • Meysam Shamshiri & Chin Kim Gan & Junainah Sardi & Mau Teng Au & Wei Hown Tee, 2020. "Design of Battery Storage System for Malaysia Low Voltage Distribution Network with the Presence of Residential Solar Photovoltaic System," Energies, MDPI, vol. 13(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4887-:d:415289
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    References listed on IDEAS

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    Cited by:

    1. Bartłomiej Mroczek & Paweł Pijarski, 2022. "Machine Learning in Operating of Low Voltage Future Grid," Energies, MDPI, vol. 15(15), pages 1-30, July.
    2. Noor Afeefah Nordin & Mohamed Nainar Mohamed Ansari & Saifuddin M. Nomanbhay & Nasri A. Hamid & Nadia M. L. Tan & Zainudin Yahya & Izhan Abdullah, 2021. "Integrating Photovoltaic (PV) Solar Cells and Supercapacitors for Sustainable Energy Devices: A Review," Energies, MDPI, vol. 14(21), pages 1-20, November.

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