Efficient energy management using fuzzy logic control in a gym microgrid with stationary bikes, PV generation, and battery storage systems

This article presents the control and energy management system for a gym microgrid that integrates multiple stationary bikes and a photovoltaic (PV) generation system connected. The main objective of this work is to investigate the feasibility of powering gym loads using the DC bus through grid-tied inverters, while ensuring efficient energy management and user-specific operation. The novelty of our approach lies in the implementation of a fuzzy logic control (FLC) strategy to achieve multiple control objectives within the gym microgrid environment, alongside a refined energy management algorithm that facilitates the flow of energy between intermittent generation sources and the variable demand from users. The system comprises several subsystems: (i) stationary bikes connected to the DC bus via AC/DC converters acting as intermittent power sources; (ii) a PV generation system interfaced through a DC-DC boost converter; (iii) gym loads. The main control objectives are as follows: (a) each stationary bike control the speed applied by the athlete to extract energy; (b) the system ensures the protection of the energy storage system by monitoring its current and voltage; (c) Extract the maximum power available from the PV system; (c) all objectives are achieved while maintaining the DC bus voltage at a specified reference value. To achieve these objectives, a fuzzy logic control approach is employed, providing adaptability and robustness in managing the dynamic behavior of the system. The system’s performance is demonstrated using the MATLAB/Simulink environment, with numerous simulations confirming that all control objectives are met.

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Publication Details

Journal
Scientific African
Published
2025-04-09
DOI
https://doi.org/10.1016/j.sciaf.2025.e02674
Citations
4
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
4.86
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article

Efficient energy management using fuzzy logic control in a gym microgrid with stationary bikes, PV generation, and battery storage systems

Abdelfattah El Azzab, Abdelmounime El Magri, Rachid Lajouad, Ilyass El Myasse
4 citations
Scientific African
Microgrid Control and Optimization
4.86
article

Efficient energy management using fuzzy logic control in a gym microgrid with stationary bikes, PV generation, and battery storage systems

Abdelfattah El Azzab, Abdelmounime El Magri, Rachid Lajouad, Ilyass El Myasse
article en
4 citations

Abstract

This article presents the control and energy management system for a gym microgrid that integrates multiple stationary bikes and a photovoltaic (PV) generation system connected. The main objective of this work is to investigate the feasibility of powering gym loads using the DC bus through grid-tied inverters, while ensuring efficient energy management and user-specific operation. The novelty of our approach lies in the implementation of a fuzzy logic control (FLC) strategy to achieve multiple control objectives within the gym microgrid environment, alongside a refined energy management algorithm that facilitates the flow of energy between intermittent generation sources and the variable demand from users. The system comprises several subsystems: (i) stationary bikes connected to the DC bus via AC/DC converters acting as intermittent power sources; (ii) a PV generation system interfaced through a DC-DC boost converter; (iii) gym loads. The main control objectives are as follows: (a) each stationary bike control the speed applied by the athlete to extract energy; (b) the system ensures the protection of the energy storage system by monitoring its current and voltage; (c) Extract the maximum power available from the PV system; (c) all objectives are achieved while maintaining the DC bus voltage at a specified reference value. To achieve these objectives, a fuzzy logic control approach is employed, providing adaptability and robustness in managing the dynamic behavior of the system. The system’s performance is demonstrated using the MATLAB/Simulink environment, with numerous simulations confirming that all control objectives are met.

Scientific AfricanVol. 28
École Normale Supérieure de l'Enseignement Technique de Mohammedia (MA), Université Hassan II Mohammedia (MA), University of Hassan II Casablanca (MA)
Affordable and clean energy
Openalex Percentile: Top 5%
Microgrid Control and Optimization
4.86
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