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Battery Energy Management System Using Edge-Driven Fuzzy Logic

Author

Listed:
  • Mustapha Habib

    (Division of Building Technology and Design, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, 11428 Stockholm, Sweden)

  • Elmar Bollin

    (Institute of Energy System Technology, Offenburg University of Applied Sciences, 77652 Offenburg, Germany)

  • Qian Wang

    (Division of Building Technology and Design, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, 11428 Stockholm, Sweden
    Uponor AB, Hackstavägen 1, 72132 Västerås, Sweden)

Abstract

Building energy management systems (BEMSs), dedicated to sustainable buildings, may have additional duties, such as hosting efficient energy management systems (EMSs) algorithms. This duty can become crucial when operating renewable energy sources (RES) and eventual electric energy storage systems (ESSs). Sophisticated EMS approaches that aim to manage RES and ESSs in real time may need high computing capabilities that BEMSs typically cannot provide. This article addresses and validates a fuzzy logic-based EMS for the optimal management of photovoltaic (PV) systems with lead-acid ESSs using an edge computing technology. The proposed method is tested on a real smart grid prototype in comparison with a classical rule-based EMS for different weather conditions. The goal is to investigate the efficacy of islanding the building local network as a control command, along with ESS power control. The results show the implementation feasibility and performance of the fuzzy algorithm in the optimal management of ESSs in both operation modes: grid-connected and islanded modes.

Suggested Citation

  • Mustapha Habib & Elmar Bollin & Qian Wang, 2023. "Battery Energy Management System Using Edge-Driven Fuzzy Logic," Energies, MDPI, vol. 16(8), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3539-:d:1127621
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    References listed on IDEAS

    as
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    4. 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.
    5. Francisco-Javier Ferrández-Pastor & Higinio Mora & Antonio Jimeno-Morenilla & Bruno Volckaert, 2018. "Deployment of IoT Edge and Fog Computing Technologies to Develop Smart Building Services," Sustainability, MDPI, vol. 10(11), pages 1-23, October.
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