The dataset contains 350 features engineered from the phasor measurements (PMU-type) signals from the IEEE New England 39-bus power system test case network, which are generated from the 9360 systematic MATLAB®/Simulink electro-mechanical transients simulations. It was prepared to serve as a convenient and open database for experimenting with different types of machine learning techniques for transient stability assessment (TSA) of electrical power systems. Different load and generation levels of the New England 39-bus benchmark power system were systematically covered, as well as all three major types of short-circuit events (three-phase, two-phase and single-phase faults) in all parts of the network. The consumed power of the network was...
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental impor...
In this paper, a Committee Neural Networks (CNN) is proposed for transient stability prediction. Tra...
This paper presents a technique that predicts the transient stability status of a power system after...
This dataset contains phasor measurements (PMU-type) signals from the IEEE New England 39-bus power ...
Many repeated manual feature adjustments and much heuristic parameter tuning are required during the...
This work employs machine learning methods to develop and test a technique for dynamic stability ana...
This paper presents transient stability assessment of a large 87-bus system using a new method calle...
In order to make full use of the dynamic information contained in the electrical quantity response t...
This paper presents transient stability assessment of electrical power system using probabilistic ne...
The purpose of this dissertation is to analyze dynamic behavior of a stressed power system and to co...
The power systems transient stability has posed significant research challenges that involve many fa...
The real-time transient stability assessment (TSA) plays a critical role in the secure operation of ...
Abstract In recent years, machine learning (ML) techniques have gained popularity in facilitating re...
Abstract Due to the wide deployment of phasor measurement unit, the real‐time assessment of transien...
Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and...
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental impor...
In this paper, a Committee Neural Networks (CNN) is proposed for transient stability prediction. Tra...
This paper presents a technique that predicts the transient stability status of a power system after...
This dataset contains phasor measurements (PMU-type) signals from the IEEE New England 39-bus power ...
Many repeated manual feature adjustments and much heuristic parameter tuning are required during the...
This work employs machine learning methods to develop and test a technique for dynamic stability ana...
This paper presents transient stability assessment of a large 87-bus system using a new method calle...
In order to make full use of the dynamic information contained in the electrical quantity response t...
This paper presents transient stability assessment of electrical power system using probabilistic ne...
The purpose of this dissertation is to analyze dynamic behavior of a stressed power system and to co...
The power systems transient stability has posed significant research challenges that involve many fa...
The real-time transient stability assessment (TSA) plays a critical role in the secure operation of ...
Abstract In recent years, machine learning (ML) techniques have gained popularity in facilitating re...
Abstract Due to the wide deployment of phasor measurement unit, the real‐time assessment of transien...
Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and...
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental impor...
In this paper, a Committee Neural Networks (CNN) is proposed for transient stability prediction. Tra...
This paper presents a technique that predicts the transient stability status of a power system after...