AI-based power system stability assessment and GUI design

• Main Author: Peng, Xuerui
• Other Authors: Xu Yan
• Format: Thesis-Master by Coursework
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Engineering::Electrical and electronic engineering::Electric power
• Online Access: https://hdl.handle.net/10356/170219
• Institution: Nanyang Technological University

This article introduces some methods of machine learning (ML) and artificial intelligence (AI) used to assess the stability of the power system. Four models are mainly used, including Support Vector Machine (SVM), Multilayer Perceptron (MLP), Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM). The four methods’ theoretical motivation is conceptually explained, and they are tested with the 7127 feature and label data. The results along with the accuracy, the recall rate, the mean absolute error as well as the mean squared error are being analyzed. During pre-processing procedure, Principal Components Analysis (PCA) is used to reduce dimension and select features. With the result of the AI model, a GUI is designed to display the label result directly.