2021
DOI: 10.3390/su132313322
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A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid

Abstract: The role of energy is cardinal for achieving the Sustainable Development Goals (SDGs) through the enhancement and modernization of energy generation and management practices. The smart grid enables efficient communication between utilities and the end- users, and enhances the user experience by monitoring and controlling the energy transmission. The smart grid deals with an enormous amount of energy data, and the absence of proper techniques for data collection, processing, monitoring and decision-making ultim… Show more

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Cited by 36 publications
(22 citation statements)
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“…The major posi-tion played by wind energy in the current and future generations will only continue to grow. Increasing cost efficiency is essential for establishing total competitiveness [53][54][55]. The decrease in operation and maintenance costs is a crucial issue in this regard in addition to sustainable economies of scale brought on by larger wind turbine designs and manufacturing advancements [56][57][58][59][60].…”
Section: Discussionmentioning
confidence: 99%
“…The major posi-tion played by wind energy in the current and future generations will only continue to grow. Increasing cost efficiency is essential for establishing total competitiveness [53][54][55]. The decrease in operation and maintenance costs is a crucial issue in this regard in addition to sustainable economies of scale brought on by larger wind turbine designs and manufacturing advancements [56][57][58][59][60].…”
Section: Discussionmentioning
confidence: 99%
“…Filling in the missing data ensures the authenticity, integrity, and accuracy of power grid business data and promotes the development of smart grid big data [60]. e optimization algorithms of optimal data parameters include the genetic algorithm [61] and the chaotic genetic optimization algorithm [62].…”
Section: Application Of Gan In Eimentioning
confidence: 99%
“…Although the volume of big data in smart grid is huge, the quality is often not high [60]. Power big data usually have low value density; that is, most of the collected data are normal sample data, and there are few abnormal data, which is the key for deep learning [66].…”
Section: Application Of Gan In Eimentioning
confidence: 99%
“…Depending on the development of big data and IoT, adapting big data analysis tools (ML/DL, data mining, statistics, etc.) can predict some potential risks, in order to mitigate accidents in the smart grid [27]. Furthermore, leveraging big data can establish a virtual smart grid environment to simulate real accidents, to investigate and develop mitigation plans.…”
Section: Introductionmentioning
confidence: 99%