Dissipativity-Based Distributed Control and Communication Topology Co-Design for Voltage Regulation and Current Sharing in DC Microgrids

This paper presents a novel dissipativity-based distributed droop-free control approach for voltage regulation and current sharing in DC microgrids (MGs) comprised of an interconnected set of distributed generators (DGs), loads, and power lines. First, we describe the closed-loop DC MG as a networked system where the DGs and lines (i.e., subsystems) are interconnected via a static interconnection matrix. This interconnection matrix demonstrates how the inputs, outputs, and disturbances of DGs and lines are connected in a DC MG. Each DG is equipped with a local controller for voltage regulation and a distributed global controller for current sharing, where the local controllers ensure individual voltage tracking while the global controllers coordinate among DGs to achieve proportional current sharing. To design the distributed global controllers, we use the dissipativity properties of the subsystems and formulate a linear matrix inequality (LMI) problem. To support the feasibility of this problem, we identify a set of necessary local and global conditions to enforce in a specifically developed LMI-based local controller design process. In contrast to existing DC MG control solutions, our approach proposes a unified framework for co-designing the distributed controller and communication topology. As the co-design process is LMI-based, it can be efficiently implemented and evaluated using existing convex optimization tools. The effectiveness of the proposed solution is verified by simulating an islanded DC MG in a MATLAB/Simulink environment under different scenarios, such as load changes and topological constraint changes, and then comparing the performance with the droop control algorithm.

Publication Details

Journal
ArXiv.org
Published
2025-03-06
Primary Topic
Microgrid Control and Optimization
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article
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article

Dissipativity-Based Distributed Control and Communication Topology Co-Design for Voltage Regulation and Current Sharing in DC Microgrids

ArXiv.org
Microgrid Control and Optimization
article

Dissipativity-Based Distributed Control and Communication Topology Co-Design for Voltage Regulation and Current Sharing in DC Microgrids

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Abstract

This paper presents a novel dissipativity-based distributed droop-free control approach for voltage regulation and current sharing in DC microgrids (MGs) comprised of an interconnected set of distributed generators (DGs), loads, and power lines. First, we describe the closed-loop DC MG as a networked system where the DGs and lines (i.e., subsystems) are interconnected via a static interconnection matrix. This interconnection matrix demonstrates how the inputs, outputs, and disturbances of DGs and lines are connected in a DC MG. Each DG is equipped with a local controller for voltage regulation and a distributed global controller for current sharing, where the local controllers ensure individual voltage tracking while the global controllers coordinate among DGs to achieve proportional current sharing. To design the distributed global controllers, we use the dissipativity properties of the subsystems and formulate a linear matrix inequality (LMI) problem. To support the feasibility of this problem, we identify a set of necessary local and global conditions to enforce in a specifically developed LMI-based local controller design process. In contrast to existing DC MG control solutions, our approach proposes a unified framework for co-designing the distributed controller and communication topology. As the co-design process is LMI-based, it can be efficiently implemented and evaluated using existing convex optimization tools. The effectiveness of the proposed solution is verified by simulating an islanded DC MG in a MATLAB/Simulink environment under different scenarios, such as load changes and topological constraint changes, and then comparing the performance with the droop control algorithm.

ArXiv.org
Openalex Percentile: Top 46%
Microgrid Control and Optimization
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