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Decision Support System for a Low Voltage Renewable Energy System

Author

Listed:
  • Iulia Stamatescu

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

  • Nicoleta Arghira

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

  • Ioana Făgărăşan

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

  • Grigore Stamatescu

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

  • Sergiu Stelian Iliescu

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

  • Vasile Calofir

    (Department of Industrial Automation and Informatics, Faculty of Automatic Control and Computers, University “Politehnica” of Bucharest, 313 Splaiul Independentei, 06004 Bucharest, Romania)

Abstract

This paper presents the development of a decision support system (DSS) for a low-voltage grid with renewable energy sources (photovoltaic panels and wind turbine) which aims at achieving energy balance in a pilot microgrid with less energy consumed from the network. The DSS is based on a procedural decision algorithm that is applied on a pilot microgrid, with energy produced from renewable energy sources, but it can be easily generalized for any microgrid. To underline the benefits of the developed DSS two case scenarios (a household and an office building with different energy consumptions) were analyzed. The results and throw added value of the paper is the description of an implemented microgrid, the development and testing of the decision support system on real measured data. Experimental results have demonstrated the validity of the approach in rule-based decision switching.

Suggested Citation

  • Iulia Stamatescu & Nicoleta Arghira & Ioana Făgărăşan & Grigore Stamatescu & Sergiu Stelian Iliescu & Vasile Calofir, 2017. "Decision Support System for a Low Voltage Renewable Energy System," Energies, MDPI, vol. 10(1), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:118-:d:88159
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    References listed on IDEAS

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    Cited by:

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    3. Ionica Oncioiu & Alina Stanciu, 2017. "An Economic Perspective on Green Energy Market in Romania," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(3), pages 102-105, September.
    4. Sławomir Francik & Adrian Knapczyk & Artur Knapczyk & Renata Francik, 2020. "Decision Support System for the Production of Miscanthus and Willow Briquettes," Energies, MDPI, vol. 13(6), pages 1-24, March.
    5. Ionica Oncioiu & Anca Gabriela Petrescu & Eugenia Grecu & Marius Petrescu, 2017. "Optimizing the Renewable Energy Potential: Myth or Future Trend in Romania," Energies, MDPI, vol. 10(6), pages 1-14, May.
    6. Daniel Icaza & David Borge-Diez & Santiago Pulla Galindo & Carlos Flores-Vázquez, 2020. "Modeling and Simulation of a Hybrid System of Solar Panels and Wind Turbines for the Supply of Autonomous Electrical Energy to Organic Architectures," Energies, MDPI, vol. 13(18), pages 1-27, September.
    7. Damilola A. Asaleye & Michael Breen & Michael D. Murphy, 2017. "A Decision Support Tool for Building Integrated Renewable Energy Microgrids Connected to a Smart Grid," Energies, MDPI, vol. 10(11), pages 1-29, November.

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