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Fuzzy Approach for Managing Renewable Energy Flows for DC-Microgrid with Composite PV-WT Generators and Energy Storage System

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  • Mario Versaci

    (DICEAM Department, “Mediterranea” University, Via Zehender, I-89122 Reggio Calabria, Italy)

  • Fabio La Foresta

    (DICEAM Department, “Mediterranea” University, Via Zehender, I-89122 Reggio Calabria, Italy)

Abstract

Recently, the implementation of software/hardware systems based on advanced artificial intelligence techniques for continuous monitoring of the electrical parameters of intelligent networks aimed at managing and controlling energy consumption has been of great interest. The contribution of this paper, starting from a recently studied DC-MG, fits into this context by proposing an intuitionistic fuzzy Takagi–Sugeno approach optimized for the energy management of isolated direct current microgrid systems consisting of a photovoltaic and a wind source. Furthermore, a lead-acid battery guarantees the stability of the DC bus while a hydrogen cell ensures the reliability of the system by avoiding blackout conditions and increasing interaction with the loads. The fuzzy rule bank, initially built using the expert’s knowledge, is optimized with the aforementioned procedure, maximizing external energy and minimizing consumption. The complete scheme, modeled using MatLab/Simulink, highlighted performance comparable to fuzzy Takagi–Sugeno systems optimized using a hybrid approach based on particle swarm optimization (to structure the antecedents of the rules) and minimum batch squares (to optimize the output).

Suggested Citation

  • Mario Versaci & Fabio La Foresta, 2024. "Fuzzy Approach for Managing Renewable Energy Flows for DC-Microgrid with Composite PV-WT Generators and Energy Storage System," Energies, MDPI, vol. 17(2), pages 1-31, January.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:2:p:402-:d:1318559
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    References listed on IDEAS

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    1. Mahmoud F. Elmorshedy & Umashankar Subramaniam & Jagabar Sathik Mohamed Ali & Dhafer Almakhles, 2023. "Energy Management of Hybrid DC Microgrid with Different Levels of DC Bus Voltage for Various Load Types," Energies, MDPI, vol. 16(14), pages 1-32, July.
    2. Fathy, Ahmed & Ferahtia, Seydali & Rezk, Hegazy & Yousri, Dalia & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid," Energy, Elsevier, vol. 247(C).
    3. Caparrós Mancera, Julio José & Saenz, Jaime Luis & López, Eduardo & Andújar, José Manuel & Segura Manzano, Francisca & Vivas, Francisco José & Isorna, Fernando, 2022. "Experimental analysis of the effects of supercapacitor banks in a renewable DC microgrid," Applied Energy, Elsevier, vol. 308(C).
    4. Uzair, Muhammad & Li, Li & Eskandari, Mohsen & Hossain, Jahangir & Zhu, Jian Guo, 2023. "Challenges, advances and future trends in AC microgrid protection: With a focus on intelligent learning methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    5. Rafati, Amir & Joorabian, Mahmood & Mashhour, Elaheh, 2020. "An efficient hour-ahead electrical load forecasting method based on innovative features," Energy, Elsevier, vol. 201(C).
    6. Zhao, Yincheng & Zhang, Guozhou & Hu, Weihao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2023. "Meta-learning based voltage control strategy for emergency faults of active distribution networks," Applied Energy, Elsevier, vol. 349(C).
    7. Areeba Naseem & Kifayat Ullah & Maria Akram & Darko Božanić & Goran Ćirović, 2022. "Assessment of Smart Grid Systems for Electricity Using Power Maclaurin Symmetric Mean Operators Based on T-Spherical Fuzzy Information," Energies, MDPI, vol. 15(21), pages 1-25, October.
    8. Carmelo Filippo Munafò & Annunziata Palumbo & Mario Versaci, 2023. "An Inhomogeneous Model for Laser Welding of Industrial Interest," Mathematics, MDPI, vol. 11(15), pages 1-25, July.
    9. Gong, Xun & Wang, Xiaozhe, 2023. "A novel Koopman-inspired method for the secondary control of microgrids with grid-forming and grid-following sources," Applied Energy, Elsevier, vol. 333(C).
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