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Exploring distributed energy generation for sustainable development: A data mining approach
School of Energy and Power Engineering, Nanjing University of Science & Technology, Nanjing, China.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.ORCID iD: 0000-0003-4720-5380
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Structural and Fire Engineering.ORCID iD: 0000-0002-5474-1512
2022 (English)In: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 48, article id 104018Article, review/survey (Refereed) Published
Abstract [en]

This study explores how data mining may be used to uncover patterns and trends in the area of distributed generation (DG). It employs the usage of the bibliometric approach. Bibliometric analysis is an increasingly common and rigorous approach for analysing huge datasets in the scientific community. It explains the evolution of a given discipline while highlighting new developments in the sector. To this purpose, this research examines the link between publishing patterns and the underlying technology trends and advances that influence these trends. Also included are key advances in the most recent findings in DG's research. The review finds that past research on system performance and optimization has built a solid conceptual framework for this research domain. The incorporation of new technologies, and the consideration of sustainability issues, are additional areas of concern. The overall strategy and methodologies utilized in this study may be applied to a wide range of research disciplines. Researchers will benefit from this study as a guide for future studies on DG integrating concerns.

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 48, article id 104018
Keywords [en]
Bibliometrics, Distributed generation, Energy storage, Grid-connected, Off-grid, On-grid, Optimization, Renewable energy
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Structural Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-89181DOI: 10.1016/j.est.2022.104018ISI: 000774188900001Scopus ID: 2-s2.0-85122796710OAI: oai:DiVA.org:ltu-89181DiVA, id: diva2:1636099
Note

Validerad;2022;Nivå 2;2022-02-09 (sofila)

Available from: 2022-02-08 Created: 2022-02-08 Last updated: 2023-09-05Bibliographically approved

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Mensah, Rhoda AfriyieDas, Oisik

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