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...

Full description

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

Internet

https://digital-library.theiet.org/content/journals/10.1049/iet-stg.2018.0043

Similar Items