Improving the data-driven transient stability assessment of power systems

thesis

posted on 2022-02-16, 23:02 authored by SEYEDALI MEGHDADI

This thesis explores the application of machine learning in predicting the transient stability of power systems.

History

Campus location

Australia

Principal supervisor

Guido Tack

Additional supervisor 1

Ariel Liebman

Additional supervisor 2

Nicolas Langrene

Year of Award

2022

Department, School or Centre

Data Science & Artificial Intelligence

Additional Institution or Organisation

Data science and AI (DSAI)

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology

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Keywords

Transfer Learning; Power System Stability; Machine Learning Knowledge Representation and Machine Learning Renewable Power and Energy Systems Engineering (excl. Solar Cells)

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