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Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis

Author

Listed:
  • Khaizaran Abdulhussein Al Sumarmad

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Nasri Sulaiman

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Noor Izzri Abdul Wahab

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

  • Hashim Hizam

    (Department of Electrical and Electronic Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Malaysia)

Abstract

Energy management and monitoring systems are significant difficulties in applying microgrids to smart homes. Thus, further research is required to address the modeling and operational parts of the system’s future results for various applications. This paper proposes a new technique for energy management in a microgrid using a robust control approach and the development of a platform for real-time monitoring. The developed controller is based on a fuzzy logic method used in the energy Internet paradigm with connected distributed generators (DGs) in the microgrid. The developed method regulates the power flow of the microgrid, and frequency/voltage regulation improved the load-management performance and monitoring system using the ThingSpeak platform for real-time data analysis. The MATLAB. simulation results show the feasibility and effectiveness of the proposed strategy and the introduced approach in microgrid control under various operating conditions. Additionally, the results show that the proposed monitoring platform facilitates real-time data analysis.

Suggested Citation

  • Khaizaran Abdulhussein Al Sumarmad & Nasri Sulaiman & Noor Izzri Abdul Wahab & Hashim Hizam, 2022. "Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis," Energies, MDPI, vol. 15(11), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:4125-:d:831304
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    References listed on IDEAS

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    2. Djamila Rekioua & Khoudir Kakouche & Abdulrahman Babqi & Zahra Mokrani & Adel Oubelaid & Toufik Rekioua & Abdelghani Azil & Enas Ali & Ali H. Kasem Alaboudy & Saad A. Mohamed Abdelwahab, 2023. "Optimized Power Management Approach for Photovoltaic Systems with Hybrid Battery-Supercapacitor Storage," Sustainability, MDPI, vol. 15(19), pages 1-30, September.
    3. Loup-Noé Lévy & Jérémie Bosom & Guillaume Guerard & Soufian Ben Amor & Marc Bui & Hai Tran, 2022. "DevOps Model Appproach for Monitoring Smart Energy Systems," Energies, MDPI, vol. 15(15), pages 1-27, July.
    4. Ziad M. Ali & Martin Calasan & Shady H. E. Abdel Aleem & Francisco Jurado & Foad H. Gandoman, 2023. "Applications of Energy Storage Systems in Enhancing Energy Management and Access in Microgrids: A Review," Energies, MDPI, vol. 16(16), pages 1-41, August.
    5. Djamila Rekioua & Toufik Rekioua & Ahmed Elsanabary & Saad Mekhilef, 2023. "Power Management Control of an Autonomous Photovoltaic/Wind Turbine/Battery System," Energies, MDPI, vol. 16(5), pages 1-24, February.

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