A machine learning based prediction method is proposed in this paper to determine the potential outage of power grid components in response to an imminent hurricane. The decision boundary, which partitions the components\u27 states into two sets of damaged and operational, is obtained via logistic regression by using a second-order function and proper parameter fitting. Two metrics are examined to validate the performance of the obtained decision boundary in efficiently predicting component outages
Typhoons can have disastrous effects on power systems. They may lead to a large number of power outa...
This letter proposes a three-dimensional Support Vector Machine (SVM) for power grid component outag...
Storms are the primary cause of extensive power outages in electric distribution networks. Storm pow...
Extreme weather events pose significant challenges to power utilities as they require very rapid dec...
Extreme weather events and natural disasters are the major cause of power outages in the United Stat...
The electrical power grid is one of modern society’s most important infrastructures and both power d...
The occurrence of the power outage caused inconvenience to the customers including the energy suppli...
Warming trends and increasing temperatures have been observed and reported by federal agencies, such...
Warming trends and increasing temperatures have been observed and reported by federal agencies, such...
We consider the problem of predicting power outages in an electrical power grid due to hazards produ...
Nowadays, a power system failure can drastically affect the reliability and normal operation of powe...
Prediction of outages in electric power systems before a hurricane can be enhanced by exploiting dat...
In the United States, weather-related power outages cost the economy tens of billions annually, and ...
A sudden extreme change in the weather can result in significant impact onthe life system in the pr...
With growing energy usage, power outages affect millions of households. This case study focuses on g...
Typhoons can have disastrous effects on power systems. They may lead to a large number of power outa...
This letter proposes a three-dimensional Support Vector Machine (SVM) for power grid component outag...
Storms are the primary cause of extensive power outages in electric distribution networks. Storm pow...
Extreme weather events pose significant challenges to power utilities as they require very rapid dec...
Extreme weather events and natural disasters are the major cause of power outages in the United Stat...
The electrical power grid is one of modern society’s most important infrastructures and both power d...
The occurrence of the power outage caused inconvenience to the customers including the energy suppli...
Warming trends and increasing temperatures have been observed and reported by federal agencies, such...
Warming trends and increasing temperatures have been observed and reported by federal agencies, such...
We consider the problem of predicting power outages in an electrical power grid due to hazards produ...
Nowadays, a power system failure can drastically affect the reliability and normal operation of powe...
Prediction of outages in electric power systems before a hurricane can be enhanced by exploiting dat...
In the United States, weather-related power outages cost the economy tens of billions annually, and ...
A sudden extreme change in the weather can result in significant impact onthe life system in the pr...
With growing energy usage, power outages affect millions of households. This case study focuses on g...
Typhoons can have disastrous effects on power systems. They may lead to a large number of power outa...
This letter proposes a three-dimensional Support Vector Machine (SVM) for power grid component outag...
Storms are the primary cause of extensive power outages in electric distribution networks. Storm pow...