AI-based power system stability assessment and GUI design
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 Me...
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Nanyang Technological University
2023
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sg-ntu-dr.10356-1702192023-09-08T15:42:29Z AI-based power system stability assessment and GUI design Peng, Xuerui Xu Yan School of Electrical and Electronic Engineering xuyan@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Electrical and electronic engineering::Electric power 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. Master of Science (Computer Control and Automation) 2023-09-04T01:52:35Z 2023-09-04T01:52:35Z 2023 Thesis-Master by Coursework Peng, X. (2023). AI-based power system stability assessment and GUI design. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/170219 https://hdl.handle.net/10356/170219 en D-257-22231-05932 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Engineering::Electrical and electronic engineering::Electric power Peng, Xuerui AI-based power system stability assessment and GUI design |
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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. |
author2 |
Xu Yan |
author_facet |
Xu Yan Peng, Xuerui |
format |
Thesis-Master by Coursework |
author |
Peng, Xuerui |
author_sort |
Peng, Xuerui |
title |
AI-based power system stability assessment and GUI design |
title_short |
AI-based power system stability assessment and GUI design |
title_full |
AI-based power system stability assessment and GUI design |
title_fullStr |
AI-based power system stability assessment and GUI design |
title_full_unstemmed |
AI-based power system stability assessment and GUI design |
title_sort |
ai-based power system stability assessment and gui design |
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Nanyang Technological University |
publishDate |
2023 |
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https://hdl.handle.net/10356/170219 |
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1779156356705550336 |