Paper Info
Title
Non-Stationary Random Process for Large-Scale Failure and Recovery of Power Distributions
Abstract
A key objective of the smart grid is to improve reliability of utility services to end users. This requires strengthening resilience of distribution networks that lie at the edge of the grid. However, distribution networks are exposed to external disturbances such as hurricanes and snow storms where electricity service to customers is disrupted repeatedly. External disturbances cause large-scale power failures that are neither well-understood, nor formulated rigorously, nor studied systematically. This work studies resilience of power distribution networks to large-scale disturbances in three aspects. First, a non-stationary random process is derived to characterize an entire life cycle of large-scale failure and recovery. Second, resilience is defined based on the non-stationary random process. Close form analytical expressions are derived under specific large-scale failure scenarios. Third, the non-stationary model and the resilience metric are applied to a real life example of large-scale disruptions due to Hurricane Ike. Real data on large-scale failures from an operational network is used to learn time-varying model parameters and resilience metrics.
Year
DOI
Venue
2012
10.4236/am.2016.73022
Applied Mathematics-a Journal of Chinese Universities Series B
Field
DocType
Volume
Psychological resilience,Mathematical optimization,Stationary random process,Electricity,Queue,Stochastic process,Severe weather,Mathematics,Grid
Journal
abs/1202.4720
Issue
Citations 
PageRank 
03
1
0.39
References 
Authors
9
6
Name
Order
Citations
PageRank
Yun Wei121.81
Chuanyi Ji2812124.04
Floyd Galvan31917.21
Stephen Couvillon421.14
George Orellana521.14
James Momoh610.73