Representational learning approach for power system transient stability assessment based on convolutional neural network
Author:
Affiliation:
1. School of Electrical EngineeringWuhan UniversityWuhanHubeiPeople's Republic of China
2. WuHan Power Supply CompanyWuhanHubeiPeople's Republic of China
3. HuNan Electric Power CorporationChangshaHunanPeople's Republic of China
Publisher
Institution of Engineering and Technology (IET)
Subject
General Engineering,Energy Engineering and Power Technology,Software
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2017.0651
Reference12 articles.
1. ZhangC. LiY. YuZ.et al.: ‘A weighted random forest approach to improve predictive performance for power system transient stability assessment’.2016 IEEE PES Asia‐Pacific Power and Energy Engineering Conf. (APPEEC) 2016 pp.1259–1263
2. Power System Transient Stability Assessment Based on Big Data and the Core Vector Machine
3. An ANN‐based multilevel classification approach using decomposed input space for transient stability assessment;Tso S.K.;Electr. Power Syst. Res.,1998
4. Support Vector Machine-Based Algorithm for Post-Fault Transient Stability Status Prediction Using Synchronized Measurements
5. Intelligent Time‐Adaptive Transient Stability Assessment System;James J.Q.;IEEE Trans. Power Syst.,2017
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