A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing

Chao-Chung Hsu, Bi-Hai Jiang and Chun-Cheng Lin ()
Additional contact information
Chao-Chung Hsu: Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
Bi-Hai Jiang: Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan
Chun-Cheng Lin: Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan

Energies, 2023, vol. 16, issue 22, 1-15

Abstract: To enable highly automated manufacturing and net-zero carbon emissions, manufacturers have invested heavily in smart manufacturing. Sustainable and smart manufacturing involves improving the efficiency and environmental sustainability of various manufacturing operations such as resource allocation, data collecting and monitoring, and process control. Recently, a lot of artificial intelligence and optimization applications based on smart grid systems have improved the energy usage efficiency in various manufacturing operations. Therefore, this survey collects recent works on applications of artificial intelligence and optimization for smart grids in smart manufacturing and analyzes their features, requirements, and challenges. In addition, potential trends and further challenges for the integration of smart grids with renewable energies for smart manufacturing, applications of 5G and B5G (beyond 5G) technologies in the SG system, and next-generation smart manufacturing systems are discussed to provide references for further research.

Keywords: smart grid; artificial intelligence; optimization techniques; smart manufacturing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/22/7660/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/22/7660/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:22:p:7660-:d:1283476

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().