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A Smart Adaptive Switching Module Architecture Using Fuzzy Logic for an Efficient Integration of Renewable Energy Sources. A Case Study of a RES System Located in Hulubești, Romania

Author

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  • Simona-Vasilica Oprea

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Romana Square 6, 010374 Bucharest, Romania)

  • Adela Bâra

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Romana Square 6, 010374 Bucharest, Romania)

  • Ștefan Preda

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Romana Square 6, 010374 Bucharest, Romania)

  • Osman Bulent Tor

    (Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Romana Square 6, 010374 Bucharest, Romania
    Engineering, Procurement, Research and Analysis—EPRA, Çankaya/Ankara 06800, Turkey)

Abstract

Electricity generation from renewable energy sources (RES) has a common feature, that is, it is fluctuating, available in certain amounts and only for some periods of time. Consuming this electricity when it is available should be a primary goal to enhance operation of the RES-powered generating units which are particularly operating in microgrids. Heavily influenced by weather parameters, RES-powered systems can benefit from implementation of sensors and fuzzy logic systems to dynamically adapt electric loads to the volatility of RES. This study attempts to answer the following question: How to efficiently integrate RES to power systems by means of sustainable energy solutions that involve sensors, fuzzy logic, and categorization of loads? A Smart Adaptive Switching Module (SASM) architecture, which efficiently uses electricity generation of local available RES by gradually switching electric appliances based on weather sensors, power forecast, storage system constraints and other parameters, is proposed. It is demonstrated that, without SASM, the RES generation is supposed to be curtailed in some cases, e.g., when batteries are fully charged, even though the weather conditions are favourable. In such cases, fuzzy rules of SASM securely mitigate curtailment of RES generation by supplying high power non-traditional storage appliances. A numerical case study is performed to demonstrate effectiveness of the proposed SASM architecture for a RES system located in Hulubești (Dâmbovița), Romania.

Suggested Citation

  • Simona-Vasilica Oprea & Adela Bâra & Ștefan Preda & Osman Bulent Tor, 2020. "A Smart Adaptive Switching Module Architecture Using Fuzzy Logic for an Efficient Integration of Renewable Energy Sources. A Case Study of a RES System Located in Hulubești, Romania," Sustainability, MDPI, vol. 12(15), pages 1-27, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:15:p:6084-:d:391300
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    References listed on IDEAS

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    1. Schieweck, Alexandra & Uhde, Erik & Salthammer, Tunga & Salthammer, Lea C. & Morawska, Lidia & Mazaheri, Mandana & Kumar, Prashant, 2018. "Smart homes and the control of indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 705-718.
    2. Apajalahti, Eeva-Lotta & Lovio, Raimo & Heiskanen, Eva, 2015. "From demand side management (DSM) to energy efficiency services: A Finnish case study," Energy Policy, Elsevier, vol. 81(C), pages 76-85.
    3. Gabriele Lobaccaro & Salvatore Carlucci & Erica Löfström, 2016. "A Review of Systems and Technologies for Smart Homes and Smart Grids," Energies, MDPI, vol. 9(5), pages 1-33, May.
    4. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    5. Aghajani, G.R. & Shayanfar, H.A. & Shayeghi, H., 2017. "Demand side management in a smart micro-grid in the presence of renewable generation and demand response," Energy, Elsevier, vol. 126(C), pages 622-637.
    6. Shehab Al-Sakkaf & Mahmoud Kassas & Muhammad Khalid & Mohammad A. Abido, 2019. "An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch," Energies, MDPI, vol. 12(8), pages 1-25, April.
    7. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
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