A Scalable Testbed for Distributed Energy Management in DC Microgrids

The increasing reliance on renewable energy sources has intensified the need for efficient energy management systems (EMS) in DC microgrids. However, existing testbeds for EMS development suffer from limitations in modularity, scalability, and cost-effectiveness, restricting their practical applicability in research and education. This study proposes a novel, scalable, and cost-effective testbed for distributed EMS in DC microgrids, integrating photovoltaic (PV) panels, wind turbines (WT), and a battery energy storage system (BESS). The testbed incorporates a bidirectional controller for optimized power flow management and physically distributed controllers for real-time energy coordination. A co-simulation framework using MATLAB/Simulink validates the system’s performance under varying operational conditions. Simulation and experimental results demonstrate an improvement in power regulation efficiency by 90%, a 80% reduction in conversion losses, and enhanced voltage stability compared to conventional models. The proposed testbed provides a versatile platform for rapid EMS prototyping, bridging the gap between theoretical research and real-world implementation. Future work will focus on expanding smart grid functionalities and incorporating machine learning-based optimization techniques.

Authors

Institutions

Publication Details

Journal
Sohag Engineering Journal/Sohag Engineering Journal
Published
2025-05-31
DOI
https://doi.org/10.21608/sej.2025.365779.1076
Citations
1
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Scalable Testbed for Distributed Energy Management in DC Microgrids

Mohamed Khamies, Khairy Sayed, Mohamed A Mohamed, Sayed Taha Sayed
1 citations
Sohag Engineering Journal/Sohag Engineering Journal
Microgrid Control and Optimization
1.21
article

A Scalable Testbed for Distributed Energy Management in DC Microgrids

Mohamed Khamies, Khairy Sayed, Mohamed A Mohamed, Sayed Taha Sayed
article en
1 citations

Abstract

The increasing reliance on renewable energy sources has intensified the need for efficient energy management systems (EMS) in DC microgrids. However, existing testbeds for EMS development suffer from limitations in modularity, scalability, and cost-effectiveness, restricting their practical applicability in research and education. This study proposes a novel, scalable, and cost-effective testbed for distributed EMS in DC microgrids, integrating photovoltaic (PV) panels, wind turbines (WT), and a battery energy storage system (BESS). The testbed incorporates a bidirectional controller for optimized power flow management and physically distributed controllers for real-time energy coordination. A co-simulation framework using MATLAB/Simulink validates the system’s performance under varying operational conditions. Simulation and experimental results demonstrate an improvement in power regulation efficiency by 90%, a 80% reduction in conversion losses, and enhanced voltage stability compared to conventional models. The proposed testbed provides a versatile platform for rapid EMS prototyping, bridging the gap between theoretical research and real-world implementation. Future work will focus on expanding smart grid functionalities and incorporating machine learning-based optimization techniques.

Sohag Engineering Journal/Sohag Engineering Journal Vol. 0(0)
Advanced Inhalation Therapies (Israel) (IL), Sohag University (EG)
Affordable and clean energy
Openalex Percentile: Top 21%
Microgrid Control and Optimization
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.