Distributed Secondary Control of DC Microgrids for Ripple Attenuation and Economic Power Sharing

ABSTRACT This paper introduces an optimized distributed secondary control framework for islanded DC microgrids that simultaneously achieves voltage regulation, economic dispatch, and voltage ripple reduction. The framework integrates consensus‐based distributed optimization to compute optimal power outputs and applies particle swarm optimization (PSO) to generate ripple‐minimizing reference signals. Both values are directly injected into the secondary control loop to adjust the system's operating point dynamically. This structure enables real‐time coordination of multiple control objectives without mutual interference, ensuring that improvements in one objective do not adversely affect the others. Simulation results on a six bus DC microgrid under varying load conditions confirm significant improvements in voltage stability, reduction of generation costs, and effective ripple suppression. The proposed approach offers a scalable, robust solution that balances technical performance with economic and power quality considerations.

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Publication Details

Journal
IET Generation Transmission & Distribution
Published
2025-01-01
DOI
https://doi.org/10.1049/gtd2.70161
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Distributed Secondary Control of DC Microgrids for Ripple Attenuation and Economic Power Sharing

Jamshid Aghaei, Sajjad Safarloo, Amirhossein Rajaei
IET Generation Transmission & Distribution
Microgrid Control and Optimization
article

Distributed Secondary Control of DC Microgrids for Ripple Attenuation and Economic Power Sharing

Jamshid Aghaei, Sajjad Safarloo, Amirhossein Rajaei
article en

Abstract

ABSTRACT This paper introduces an optimized distributed secondary control framework for islanded DC microgrids that simultaneously achieves voltage regulation, economic dispatch, and voltage ripple reduction. The framework integrates consensus‐based distributed optimization to compute optimal power outputs and applies particle swarm optimization (PSO) to generate ripple‐minimizing reference signals. Both values are directly injected into the secondary control loop to adjust the system's operating point dynamically. This structure enables real‐time coordination of multiple control objectives without mutual interference, ensuring that improvements in one objective do not adversely affect the others. Simulation results on a six bus DC microgrid under varying load conditions confirm significant improvements in voltage stability, reduction of generation costs, and effective ripple suppression. The proposed approach offers a scalable, robust solution that balances technical performance with economic and power quality considerations.

IET Generation Transmission & DistributionVol. 19(1)
Shiraz University of Technology (IR), Central Queensland University (AU)
Openalex Percentile: Top 66%
Microgrid Control and Optimization
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