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IEEE New England 39-bus test case: Dataset for the Transient Stability Assessment (CROSBI ID 792591)

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Sarajcev, Petar ; Kunac, Antonijo ; Petrovic, Goran ; Despalatovic, Marin IEEE New England 39-bus test case: Dataset for the Transient Stability Assessment // Zenodo. 2022.

Podaci o odgovornosti

Sarajcev, Petar ; Kunac, Antonijo ; Petrovic, Goran ; Despalatovic, Marin

engleski

IEEE New England 39-bus test case: Dataset for the Transient Stability Assessment

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 set to 80%, 90%, 100%, 110% and 120% of the basic system load levels. The short-circuits were located on the busbar or on the transmission line (TL). When they were located on a TL, it was assumed that they can occur at 20%, 40%, 60%, and 80% of the line length. Features were obtained directly from the time-domain signals at the pickup time (pre-fault value) and at the trip time (post-fault value) of the associated distance protection relays. This is a stochastic dataset of 3120 cases, created from the population of 9360 systematic simulations, which features a statistical distribution of different fault types, as follows: single-phase (70%), double-phase (20%) and three-phase faults (10%). It also features a class imbalance, with less than 20% of cases belonging to the unstable class.

dataset ; power system ; transient stability ; New England 39-bus ; machine learning ; class imbalance

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Podaci o izdanju

Zenodo

2022.

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objavljeno

Povezanost rada

Elektrotehnika

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