Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Ahsan, F; Dana, NH; Sarker, SK; Li, L; Muyeen, SM; Ali, MF; Tasneem, Z; Hasan, MM; Abhi, SH; Islam, MR; Ahamed, MH; Islam, MM; Das, SK; Badal, MFR; Das, P

Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

Ahsan, F Dana, NH Sarker, SK Li, L

Muyeen, SM Ali, MF Tasneem, Z Hasan, MM Abhi, SH Islam, MR Ahamed, MH Islam, MM Das, SK Badal, MFR Das, P

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Publisher:: SPRINGER SINGAPORE PTE LTD
Publication Type:: Journal Article
Citation:: Protection and Control of Modern Power Systems, 2023, 8, (1)
Issue Date:: 2023-12-01

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Field	Value	Language
dc.contributor.author	Ahsan, F
dc.contributor.author	Dana, NH
dc.contributor.author	Sarker, SK
dc.contributor.author	Li, L https://orcid.org/0000-0001-8485-2216
dc.contributor.author	Muyeen, SM
dc.contributor.author	Ali, MF
dc.contributor.author	Tasneem, Z
dc.contributor.author	Hasan, MM
dc.contributor.author	Abhi, SH
dc.contributor.author	Islam, MR
dc.contributor.author	Ahamed, MH
dc.contributor.author	Islam, MM
dc.contributor.author	Das, SK
dc.contributor.author	Badal, MFR
dc.contributor.author	Das, P
dc.date.accessioned	2024-04-11T20:19:22Z
dc.date.available	2024-04-11T20:19:22Z
dc.date.issued	2023-12-01
dc.identifier.citation	Protection and Control of Modern Power Systems, 2023, 8, (1)
dc.identifier.issn	2367-2617
dc.identifier.issn	2367-0983
dc.identifier.uri	http://hdl.handle.net/10453/177772
dc.description.abstract	Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efficient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efficient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can offer extended support for engineers and researchers in the context of data-driven technology and the SG.
dc.language	English
dc.publisher	SPRINGER SINGAPORE PTE LTD
dc.relation.ispartof	Protection and Control of Modern Power Systems
dc.relation.isbasedon	10.1186/s41601-023-00319-5
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.rights	© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0
dc.title	Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
dc.type	Journal Article
utslib.citation.volume	8
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	open_access	*
dc.date.updated	2024-04-11T20:19:19Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	8
utslib.citation.issue	1

Abstract:

Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efficient energy generation, transmission, and distribution. After conducting thorough research for more than a decade, the concept of the smart grid (SG) has emerged, and its practice around the world paves the ways for efficient use of reliable energy technology. However, many developing features evoke keen interest and their improvements can be regarded as the next-generation smart grid (NGSG). Also, to deal with the non-linearity and uncertainty, the emergence of data-driven NGSG technology can become a great initiative to reduce the diverse impact of non-linearity. This paper exhibits the conceptual framework of NGSG by enabling some intelligent technical features to ensure its reliable operation, including intelligent control, agent-based energy conversion, edge computing for energy management, internet of things (IoT) enabled inverter, agent-oriented demand side management, etc. Also, a study on the development of data-driven NGSG is discussed to facilitate the use of emerging data-driven techniques (DDTs) for the sustainable operation of the SG. The prospects of DDTs in the NGSG and their adaptation challenges in real-time are also explored in this paper from various points of view including engineering, technology, et al. Finally, the trends of DDTs towards securing sustainable and clean energy evolution from the NGSG technology in order to keep the environment safe is also studied, while some major future issues are highlighted. This paper can offer extended support for engineers and researchers in the context of data-driven technology and the SG.

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http://hdl.handle.net/10453/177772