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ISSN:
2315-4462 (Print); 2373-3594 (Online)
Abbreviated Title:
Int. J Smart Grid Clean Energy
Frequency:
4 issues per year
Editor-in-Chief:
Prof. Danny Sutanto
DOI:
10.12720/sgce
APC:
500 USD
Indexed by:
Inspec (IET),
CNKI
, Crossref, Google Scholar,
etc
.
Editor-in-Chief
Prof. Danny Sutanto
University of Wollongong, Australia
I am very excited to serve as the first Editor-in-Chief of the Journal of Smart Grid and Clean Energy (IJSGCE)and hope that the publication can enrich the readers’ experience .... [
Read More
]
What's New
2024-03-28
March 28th, 2024 News! Vol. 13, No. 1 has been published online!
2024-01-04
IJSGCE will adopt Article-by-Article Work Flow. For the quarterly journal, each issue will be released at the end of the issue month.
2023-10-09
October 9th, 2023 News! Vol. 11, No. 4 has been published online!
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2022
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Vol. 11, No. 2, April 2022
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The design of a novel smart home control system using a smart grid based on edge and cloud computing
Author(s): Mais Nijim, Divya Ballampalli
Texas A&M University Kingsville, 700 University Blvd., Kingsville 78363, USA
International Journal of Smart Grid and Clean Energy
, vol. 11, no. 2, April 2022: pp. 57-71
Digital Object Identifier: 10.12720/sgce.11.2.57-71
Abstract
: The Internet of Things (IoTs) has transpired as a fascinating technology for smart cities, smart homes, and smart grids using a vast amount of IoT data. A smart grid is one of the core components where transport, generation, delivery, and electricity consumption are enhanced in terms of protection and reliability. The existing power grid is suffering from many problems such as outages and unpredictable power disturbances, inflexible energy rates, unnoticeable customer fraud, and many other disadvantages. These problems lead to the ever-rising demand for fossil fuel and service costs. For example, the peak hour demand needs to be overestimated and more energy generated to minimize the risk of an outage. The main problem of the smart grid is the tremendous amount of data needs to be collected from the IoTs devices, and processing the data is a challenge. Using and predicting a large amount of data in smart Grid and IoTs is still in its infancy. To remedy this problem, we propose a hybrid solution by using the Cloud and Edge Computing to process the data. We define a hybrid solution where we use the edge computing for the smart grid information processing where the microgrids are located on the edge of the IoTs network and on the Cloud to be used for the power grid that distributes power to the microgrids. Additionally, we proposed a machine learning engine to establish the communication between the edge layer, failover between edges, and the Cloud layer.
Keywords
: smart grid, edge computing, machine learning
Full Paper.pdf
Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (
CC BY-NC-ND 4.0
), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
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