A Self-Organizing Multi-Agent System for Distributed Voltage Regulation

This paper presents a distributed voltage regulation method based on multi-agent system control and network self-organization for a large distribution network. The network autonomously organizes itself into small subnetworks through the epsilon decomposition of the sensitivity matrix, and agents gro...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2021-09, Vol.12 (5), p.4102-4112
Main Authors: Faiya, Badr Al, Athanasiadis, Dimitrios, Chen, Minjiang, McArthur, Stephen, Kockar, Ivana, Lu, Haowei, de Leon, Francisco
Format: Article
Language:English
Subjects:
Distributed generation
distributed voltage regulation
Distribution networks
Electric potential
epsilon decomposition
Jacobian matrices
Matrix decomposition
multi-agent systems
Multiagent systems
Optimization
Power system dynamics
Reactive power
self-organization
Sensitivity
Voltage
Voltage control
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Summary:This paper presents a distributed voltage regulation method based on multi-agent system control and network self-organization for a large distribution network. The network autonomously organizes itself into small subnetworks through the epsilon decomposition of the sensitivity matrix, and agents group themselves into these subnetworks with the communication links being autonomously determined. Each subnetwork controls its voltage by locating the closest local distributed generation and optimizing their outputs. This simplifies and reduces the size of the optimization problem and the interaction requirements. This approach also facilitates adaptive grouping of the network by self-reorganizing to maintain a stable state in response to time-varying network requirements and changes. The effectiveness of the proposed approach is validated through simulations on a model of a real heavily-meshed secondary distribution network. Simulation results and comparisons with other methods demonstrate the ability of the subnetworks to autonomously and independently regulate the voltage and to adapt to unpredictable network conditions over time, thereby enabling autonomous and flexible distribution networks.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2021.3070783