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Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings

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  • Yerasimos Yerasimou

    (PV Technology Laboratory, FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus)

  • Marios Kynigos

    (PV Technology Laboratory, FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus)

  • Venizelos Efthymiou

    (PV Technology Laboratory, FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus)

  • George E. Georghiou

    (PV Technology Laboratory, FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus)

Abstract

Distributed generation (DG) systems are growing in number, diversifying in driving technologies and providing substantial energy quantities in covering the energy needs of the interconnected system in an optimal way. This evolution of technologies is a response to the needs of the energy transition to a low carbon economy. A nanogrid is dependent on local resources through appropriate DG, confined within the boundaries of an energy domain not exceeding 100 kW of power. It can be a single building that is equipped with a local electricity generation to fulfil the building’s load consumption requirements, it is electrically interconnected with the external power system and it can optionally be equipped with a storage system. It is, however, mandatory that a nanogrid is equipped with a controller for optimisation of the production/consumption curves. This study presents design consideretions for nanogrids and the design of a nanogrid system consisting of a 40 kWp photovoltaic (PV) system and a 50 kWh battery energy storage system (BESS) managed via a central converter able to perform demand-side management (DSM). The implementation of the nanogrid aims at reducing the CO 2 footprint of the confined domain and increase its self-sufficiency.

Suggested Citation

  • Yerasimos Yerasimou & Marios Kynigos & Venizelos Efthymiou & George E. Georghiou, 2021. "Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings," Energies, MDPI, vol. 14(12), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3683-:d:578677
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    References listed on IDEAS

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    Cited by:

    1. Muhammed Shahid & Rizwan Aslam Butt & Attaullah Khawaja, 2022. "Fiscal- and Space-Constrained Energy Optimization Model for Hybrid Grid-Tied Solar Nanogrids," Energies, MDPI, vol. 15(21), pages 1-15, October.
    2. Arsalis, Alexandros & Papanastasiou, Panos & Georghiou, George E., 2022. "A comparative review of lithium-ion battery and regenerative hydrogen fuel cell technologies for integration with photovoltaic applications," Renewable Energy, Elsevier, vol. 191(C), pages 943-960.
    3. Seif Khiati & Rafik Belarbi & Ammar Yahia, 2023. "Sustainable Buildings: A Choice, or a Must for Our Future?," Energies, MDPI, vol. 16(6), pages 1-5, March.
    4. Akash Kumar & Bing Yan & Ace Bilton, 2022. "Machine Learning-Based Load Forecasting for Nanogrid Peak Load Cost Reduction," Energies, MDPI, vol. 15(18), pages 1-23, September.

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