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AuthorAhsan, Faiaz
AuthorDana, Nazia Hasan
AuthorSarker, Subrata K.
AuthorLi, Li
AuthorMuyeen, S. M.
AuthorAli, Md Firoj
AuthorTasneem, Zinat
AuthorHasan, Md Mehedi
AuthorAbhi, Sarafat Hussain
AuthorIslam, Md Robiul
AuthorAhamed, Md Hafiz
AuthorIslam, Md Manirul
AuthorDas, Sajal K.
AuthorBadal, Md Faisal R.
AuthorDas, Prangon
Available date2025-01-13T09:06:45Z
Publication Date2023-12
Publication NameProtection and Control of Modern Power Systems
Identifierhttp://dx.doi.org/10.1186/s41601-023-00319-5
CitationAhsan, F., Dana, N. H., Sarker, S. K., Li, L., Muyeen, S. M., Ali, M. F., ... & Das, P. (2023). Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review. Protection and Control of Modern Power Systems, 8(3), 1-42.
ISSN2367-2617
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85169978804&origin=inward
URIhttp://hdl.handle.net/10576/62128
AbstractMeteorological 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.
Languageen
SubjectAnd Machine learning technique
Data-driven technology
Intelligent management
Next-generation smart grid
Smart grid
Sustainable energy evolution
TitleData-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review
TypeArticle
Pagination1-42
Issue Number1
Volume Number8
ESSN2367-0983
dc.accessType Open Access


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