Design and implementation of a hierarchical hybrid communication platform for multi-microgrid applications

Jamborsalamati, P; Moghimi, M; Hossain, J; Lu, J

Design and implementation of a hierarchical hybrid communication platform for multi-microgrid applications

Jamborsalamati, P Moghimi, M Hossain, J

Lu, J

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Publication Type:: Conference Proceeding
Citation:: Smart Innovation, Systems and Technologies, 2019, 131 pp. 199 - 208
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Jamborsalamati, P	en_US
dc.contributor.author	Moghimi, M	en_US
dc.contributor.author	Hossain, J https://orcid.org/0000-0001-7602-3581	en_US
dc.contributor.author	Lu, J	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Smart Innovation, Systems and Technologies, 2019, 131 pp. 199 - 208	en_US
dc.identifier.isbn	9783030042929	en_US
dc.identifier.issn	2190-3018	en_US
dc.identifier.uri	http://hdl.handle.net/10453/138653
dc.description.abstract	© Springer Nature Switzerland AG 2019. This paper presents a hierarchical hybrid communication platform for Multi-Microgrid (MMG) optimization applications. The main purpose of the implemented platform is to attach multiple Microgrids (MGs) to each other by adding an Internet of Things (IoT) gateway to each MG. This enables bi-directional data exchange among the MGs through the IoT gateway for optimal operation of the MGs with respect to each other. Considering the scale of the data acquisition in MMG optimization problems, utilization of a cloud-based platform for extensive data sharing and post-processing of the aggregated data is vital. The proposed platform has adopted Modbus protocol for communications between the devices inside each MG, local controllers, and the MG Central Controller (MGCC). The Message Queue Telemetry Transport (MQTT) protocol is used for data sharing among the MGCCs and HTTP requests for interactions with a cloud server in a hybrid platform. The cloud server has an interface to MATLAB and the hierarchical architecture is implemented in a co-simulation platform with Python and MATLAB. Results show the efficacy of the implemented platform for MMG optimization applications.	en_US
dc.relation.ispartof	Smart Innovation, Systems and Technologies	en_US
dc.relation.isbasedon	10.1007/978-3-030-04293-6_20	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Design and implementation of a hierarchical hybrid communication platform for multi-microgrid applications	en_US
dc.type	Conference Proceeding
utslib.citation.volume	131	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US
pubs.volume	131	en_US

Abstract:

© Springer Nature Switzerland AG 2019. This paper presents a hierarchical hybrid communication platform for Multi-Microgrid (MMG) optimization applications. The main purpose of the implemented platform is to attach multiple Microgrids (MGs) to each other by adding an Internet of Things (IoT) gateway to each MG. This enables bi-directional data exchange among the MGs through the IoT gateway for optimal operation of the MGs with respect to each other. Considering the scale of the data acquisition in MMG optimization problems, utilization of a cloud-based platform for extensive data sharing and post-processing of the aggregated data is vital. The proposed platform has adopted Modbus protocol for communications between the devices inside each MG, local controllers, and the MG Central Controller (MGCC). The Message Queue Telemetry Transport (MQTT) protocol is used for data sharing among the MGCCs and HTTP requests for interactions with a cloud server in a hybrid platform. The cloud server has an interface to MATLAB and the hierarchical architecture is implemented in a co-simulation platform with Python and MATLAB. Results show the efficacy of the implemented platform for MMG optimization applications.

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http://hdl.handle.net/10453/138653