Machine learning based energy management system for grid disaster mitigation

Machine learning based energy management system for grid disaster mitigation

The recent increase in infiltration of distributed resources has challenged the traditional operation of power systems. Simultaneously, devastating effects of recent natural disasters have questioned the resilience of power infrastructure for an electricity dependent community. In this study, a solu...

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Bibliographic Details
Main Authors:	Lizon Maharjan, Mark Ditsworth, Manish Niraula, Carlos Caicedo Narvaez, Babak Fahimi
Format:	Article
Language:	English
Published:	Wiley 2018-12-01
Series:	IET Smart Grid
Subjects:	energy management systems disasters power engineering computing building management systems power grids distributed power generation learning (artificial intelligence) smart power grids machine learning based energy management system grid disaster mitigation recent increase infiltration distributed resources traditional operation power systems recent natural disasters resilience power infrastructure electricity dependent community resilient smart grid network power availability disastrous events power electronics load categorisation features presented system utilises ML tools smart grid design process
Online Access:	https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2018.0043

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