Deep Learning Method for Power System Generator Tripping Assessment
碩士 === 國立臺灣海洋大學 === 電機工程學系 === 106 === The main purpose of this thesis is to use Deep Learning method to determine that which load shedding can let the system recover stable and decide the better load to be shed. When the generator tripping occurs in the system may be affected the voltage, frequency...
Main Authors: | Lai, Kuan-Ting, 賴冠廷 |
---|---|
Other Authors: | Huang, Pei-Hwa |
Format: | Others |
Language: | zh-TW |
Published: |
2018
|
Online Access: | http://ndltd.ncl.edu.tw/handle/68qw2v |
Similar Items
-
Dialog Action Decision Using Deep Reinforcement Learning for Question Generation in an Interview Coaching System
by: Kuan-JungLai, et al.
Published: (2016) -
An approach of Estimating Truck Trip Generation
by: Lai, Chih-Yi, et al.
Published: (2009) -
RELIABILITY ANALYSIS OF WIND POWER GENERATION GRID CONNECTION USING FAULT TREE METHOD
by: Kuan-Liang Lai, et al.
Published: (2005) -
Deep Factorized and Variational Learning for Source Separation
by: Kuo, Kuan-Ting, et al.
Published: (2016) -
Support Vector Machine Classification Analysis for Power System Generator Tripping
by: Chen,Yong-Yan, et al.
Published: (2018)