The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
IoT-enabled smart grid via SM: An overview
Open accessAbstract
Abstract Power quality and reliability issues are big challenges to both service provider and consumers in conventional power grids. The ongoing technological advancements in the Internet of Things (IoT) era provide better solutions to enhance the management of these challenges and enforce the measures of a Smart Grid (SG). Advanced Metering Infrastructure (AMI) and Smart Metering (SM) technologies are enabler technologies that can modernize the conventional power grid through exposing the hidden details of electrical power by introducing two-way communication scheme during power transaction process between utilities and consumers. Throughout literature, AMI and SM technologies are widely discussed. However, few studies discuss the role of SM in power quality and reliability monitoring in IoT-enabled SGs. Hence, the paper aims to comprehensively review the feasibility of employing SM for power quality and reliability monitoring. First, we provide a detailed overview about the SMs, wireless communication technologies, and routing algorithms as enabling technologies in AMI. Then, we categorize the existing literature works that target power quality and reliability monitoring. Finally, open research issues are outlined based on shortages in the existing literature.
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1 retracted
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A survey on LPWA technology: LoRa and NB-IoT
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A survey on the communication architectures in smart grid
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A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues
Stoyanova, M., Nikoloudakis, Y., Panagiotakis, S., Pallis, E., & Markakis, E. K. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2962586 · Cited by 852
Using the internet of things in smart energy systems and networks
Ahmad, T., & Zhang, D. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.102783 · Cited by 332
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Metadata
- Authors
- Al-Turjman, F., & Abujubbeh, M.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 96
- Pages
- 579-590
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2911489589
- Cited by
- 319
- References
- 55
- FWCI
- 15.69
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
