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A survey of intelligent load monitoring in IoT-enabled distributed smart grids

Gan, Jixiang; Zeng, Lei; Liu, Qi; Liu, Xiaodong

Authors

Jixiang Gan

Lei Zeng

Qi Liu



Abstract

Power load monitoring has been a research hotspot since a few years ago. With development of artificial intelligence, construction of smart grid has become the most important part of power load monitoring. At the same time, task scheduling mechanism combined with the distributed internet of things (IoT) improves efficiency of smart grid. In this paper, applications of cloud/edge platform in the data acquisition, processing and scheduling of the IoT is introduced step by step, as well as applications and differences of artificial intelligence algorithm in each step, including data acquisition, load disaggregation, load forecasting and so on. Finally, combined with various optimisation methods, future research directions are prospected, including data and network security issues, and challenges faced by cloud/edge architecture, adaptive fine-grained load disaggregation, and load forecasting.

Journal Article Type Article
Acceptance Date Oct 31, 2022
Online Publication Date Dec 7, 2022
Publication Date 2023
Deposit Date Jan 27, 2023
Publicly Available Date Dec 8, 2023
Journal International Journal of Ad Hoc and Ubiquitous Computing
Print ISSN 1743-8225
Electronic ISSN 1743-8233
Publisher Inderscience
Peer Reviewed Peer Reviewed
Volume 42
Issue 1
Pages 12
DOI https://doi.org/10.1504/ijahuc.2023.127781
Keywords Internet of Things, IoT, smart grids, artificial intelligence, load disaggregation, load forecasting
Public URL http://researchrepository.napier.ac.uk/Output/3011503

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