Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication
Abstract The secondary control layer of microgrids is often modelled as a multi‐agent distributed system, coordinated based on consensus protocols. Convergence time of consensus algorithm significantly affects transient stability of microgrids, due to changes in communication topology, switching of...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Wiley
2022-01-01
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Series: | IET Generation, Transmission & Distribution |
Subjects: | |
Online Access: | https://doi.org/10.1049/gtd2.12284 |
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author | Seyed Amir Alavi Ardavan Rahimian Kamyar Mehran Vahid Vahidinasab |
author_facet | Seyed Amir Alavi Ardavan Rahimian Kamyar Mehran Vahid Vahidinasab |
author_sort | Seyed Amir Alavi |
collection | DOAJ |
description | Abstract The secondary control layer of microgrids is often modelled as a multi‐agent distributed system, coordinated based on consensus protocols. Convergence time of consensus algorithm significantly affects transient stability of microgrids, due to changes in communication topology, switching of distributed generations (DGs), and uncertainty of intermittent energy sources. To minimise convergence time in consensus protocol, this work proposes a multilayer event‐based consensus control framework, which is resilient to communication delays and supports plug‐and‐play (P&P) addition or removal of DGs in DC microgrids of cellular energy systems. A novel bi‐layer optimisation algorithm minimises convergence time by selecting an optimal communication topology graph and then adjusts controllers' parameters. Average consensus is achieved among distributed controllers using an event‐based consensus protocol, considering non‐uniform delays between agents. A realisation method has also been introduced using the directional beamforming technique for topology assignment algorithm based on modern telecommunication technologies. Provided feasibility case study has been implemented on a real‐time hardware‐in‐the‐loop (HIL) experimental testbed, to validate the performance of the proposed framework for key purposes of voltage stabilisation and balanced power‐sharing in DC microgrids. |
first_indexed | 2024-04-11T09:54:35Z |
format | Article |
id | doaj.art-f24f80cb55d04aef8bb9c89619475542 |
institution | Directory Open Access Journal |
issn | 1751-8687 1751-8695 |
language | English |
last_indexed | 2024-04-11T09:54:35Z |
publishDate | 2022-01-01 |
publisher | Wiley |
record_format | Article |
series | IET Generation, Transmission & Distribution |
spelling | doaj.art-f24f80cb55d04aef8bb9c896194755422022-12-22T04:30:42ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952022-01-0116226728110.1049/gtd2.12284Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communicationSeyed Amir Alavi0Ardavan Rahimian1Kamyar Mehran2Vahid Vahidinasab3School of Electronic Engineering and Computer Science Queen Mary University of London London UKSchool of Engineering Ulster University Newtownabbey UKSchool of Electronic Engineering and Computer Science Queen Mary University of London London UKDepartment of Engineering, School of Science and Technology Nottingham Trent University Nottingham UKAbstract The secondary control layer of microgrids is often modelled as a multi‐agent distributed system, coordinated based on consensus protocols. Convergence time of consensus algorithm significantly affects transient stability of microgrids, due to changes in communication topology, switching of distributed generations (DGs), and uncertainty of intermittent energy sources. To minimise convergence time in consensus protocol, this work proposes a multilayer event‐based consensus control framework, which is resilient to communication delays and supports plug‐and‐play (P&P) addition or removal of DGs in DC microgrids of cellular energy systems. A novel bi‐layer optimisation algorithm minimises convergence time by selecting an optimal communication topology graph and then adjusts controllers' parameters. Average consensus is achieved among distributed controllers using an event‐based consensus protocol, considering non‐uniform delays between agents. A realisation method has also been introduced using the directional beamforming technique for topology assignment algorithm based on modern telecommunication technologies. Provided feasibility case study has been implemented on a real‐time hardware‐in‐the‐loop (HIL) experimental testbed, to validate the performance of the proposed framework for key purposes of voltage stabilisation and balanced power‐sharing in DC microgrids.https://doi.org/10.1049/gtd2.12284Combinatorial mathematicsOptimisation techniquesSignal processing and detectionProtocolsCommunication network design, planning and routingCombinatorial mathematics |
spellingShingle | Seyed Amir Alavi Ardavan Rahimian Kamyar Mehran Vahid Vahidinasab Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication IET Generation, Transmission & Distribution Combinatorial mathematics Optimisation techniques Signal processing and detection Protocols Communication network design, planning and routing Combinatorial mathematics |
title | Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication |
title_full | Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication |
title_fullStr | Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication |
title_full_unstemmed | Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication |
title_short | Multilayer event‐based distributed control system for DC microgrids with non‐uniform delays and directional communication |
title_sort | multilayer event based distributed control system for dc microgrids with non uniform delays and directional communication |
topic | Combinatorial mathematics Optimisation techniques Signal processing and detection Protocols Communication network design, planning and routing Combinatorial mathematics |
url | https://doi.org/10.1049/gtd2.12284 |
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