A multi-agent system approach for real-time energy management and control in hybrid low-voltage microgrids

The real-time operation of microgrids is crucial due to its ability to enhance energy resilience and efficiency. Continuous monitoring and adaptation to fluctuations in energy supply and demand ensure a stable and reliable electricity supply to local communities, even in the case of grid disturbances. This article presents an efficient and easily implementable real-time energy management and control system based on multi-agent systems for hybrid Low-Voltage Micro-Grids (LVMGs) using energy storage systems and renewable sources. The main objective of the proposed approach is to determine optimal setpoints for all microgrid components to improve overall efficiency and reduce electricity costs while satisfying multiple constraints. The well-defined flexibilities of all microgrid components to adjust their power are exploited to achieve optimal power allocation. The approach is tested and validated by developing a simulation environment using the Java Agent Development (JADE) framework, enabling the implementation of microgrid optimization through MATLAB/Simulink. • Multi-Agent System (MAS) Efficiency: Multi-Agent Systems improve energy management flexibility and efficiency in hybrid microgrids via decentralized decision-making. • Real-Time Energy Management: Real-time control ensures continuous monitoring and adapts to energy fluctuations, boosting resilience and reliability. • Integration of Renewable Energy Sources: Integrates solar, wind, and storage systems to optimize energy demands and maximize renewable benefits. • Simulation and Validation: Tested with JADE and MATLAB/Simulink to optimize microgrid operations and improve overall efficiency. • Key Performance Indicators (KPIs): Key KPIs include energy production, consumption, cost index, and efficiency under various energy management scenarios.

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Publication Details

Journal
Results in Engineering
Published
2024-10-04
DOI
https://doi.org/10.1016/j.rineng.2024.103035
Citations
29
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
9.52
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article

A multi-agent system approach for real-time energy management and control in hybrid low-voltage microgrids

Abdelmounime El Magri, Rachid Lajouad, Soukaina Boudoudouh, Doha El Hafiane et al.
29 citations
Results in Engineering
Microgrid Control and Optimization
9.52
article

A multi-agent system approach for real-time energy management and control in hybrid low-voltage microgrids

Abdelmounime El Magri, Rachid Lajouad, Soukaina Boudoudouh, Doha El Hafiane, Houssam Eddine Chakir
article en
29 citations

Abstract

The real-time operation of microgrids is crucial due to its ability to enhance energy resilience and efficiency. Continuous monitoring and adaptation to fluctuations in energy supply and demand ensure a stable and reliable electricity supply to local communities, even in the case of grid disturbances. This article presents an efficient and easily implementable real-time energy management and control system based on multi-agent systems for hybrid Low-Voltage Micro-Grids (LVMGs) using energy storage systems and renewable sources. The main objective of the proposed approach is to determine optimal setpoints for all microgrid components to improve overall efficiency and reduce electricity costs while satisfying multiple constraints. The well-defined flexibilities of all microgrid components to adjust their power are exploited to achieve optimal power allocation. The approach is tested and validated by developing a simulation environment using the Java Agent Development (JADE) framework, enabling the implementation of microgrid optimization through MATLAB/Simulink. • Multi-Agent System (MAS) Efficiency: Multi-Agent Systems improve energy management flexibility and efficiency in hybrid microgrids via decentralized decision-making. • Real-Time Energy Management: Real-time control ensures continuous monitoring and adapts to energy fluctuations, boosting resilience and reliability. • Integration of Renewable Energy Sources: Integrates solar, wind, and storage systems to optimize energy demands and maximize renewable benefits. • Simulation and Validation: Tested with JADE and MATLAB/Simulink to optimize microgrid operations and improve overall efficiency. • Key Performance Indicators (KPIs): Key KPIs include energy production, consumption, cost index, and efficiency under various energy management scenarios.

Results in EngineeringVol. 24
Institut of Research in Solar Energy and New Energies (MA), University of Hassan II Casablanca (MA)
Affordable and clean energy
Openalex Percentile: Top 1%
Microgrid Control and Optimization
9.52
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