The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
5G network-based Internet of Things for demand response in smart grid: A survey on application potential
Abstract
Demand response (DR) has been widely regarded as an effective way to provide regulation services for smart grids by controlling demand-side resources via new and improved information and communication technologies. Emerging 5G networks and 5G-based Internet of Things (IoTs) can doubtless provide better infrastructure for DR, owing to 5G’s advantages of fast transfer speed, high reliability, robust security, low power consumption, and massive number of connections. However, nearly none of the existing studies have applied 5G technology to DR, which will be the subject surveyed in this paper. First, the concept of DR and recent practical advances are investigated, especially the application of communication technologies to DR. Then, a comprehensive review of the cyber security, consumer privacy, and reliability of DR is presented. These topics received little attention in the past, but they will be among the most crucial factors in the future. In addition, the essential features and typical application scenarios of 5G communication are investigated. On this basis, the advantages, methods, recent advances, and implementation planning of 5G on DR are studied. Finally, the future work that must urgently be conducted in order to achieve the application of 5G to DR is discussed. This paper’s application survey of 5G on DR is carried out before 5G technology enters the large-scale commercial stage, so as to provide references and guidelines for developing future 5G networks in the smart grid paradigm.
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Cites
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Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2021.125834 · Cited by 1,258
Self-citationInternet of Things (IoT) and the Energy Sector
Hossein Motlagh, N., Mohammadrezaei, M., Hunt, J., & Zakeri, B. (2020) · Energies · doi:10.3390/en13020494 · Cited by 772
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Ibrahim, M. S., Dong, W., & Yang, Q. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115237 · Cited by 435
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Palomares, I., Martínez-Cámara, E., Montes, R., García-Moral, P., Chiachio, M., Chiachio, J., Alonso, S., Melero, F. J., Molina, D., Fernández, B., et al. (2021) · Applied Intelligence · doi:10.1007/s10489-021-02264-y · Cited by 276
Metadata
- Authors
- Hui, H., Ding, Y., Shi, Q., Li, F., Song, Y., & Yan, J.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 257
- Pages
- 113972
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2981573690
- Cited by
- 373
- References
- 57
- FWCI
- 16.04
- Type
- journal article
- Language
- en
- Open access
- closed
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