PMU Measurements-Based Short-Term Voltage Stability Assessment of Power Systems via Deep Transfer Learning-Reference-Cited by-同舟云学术

PMU Measurements-Based Short-Term Voltage Stability Assessment of Power Systems via Deep Transfer Learning

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li Yang¹^ORCID,Zhang Shitu¹^ORCID,Li Yuanzheng²^ORCID,Cao Jiting³^ORCID,Jia Shuyue⁴^ORCID

Affiliation:

1. School of Electrical Engineering, Northeast Electric Power University, Jilin, China

2. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China

3. State Grid Chengde Power Supply Company, Chengde, China

4. Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA

Funder

Natural Science Foundation of Jilin Province, China

Open Project of Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology, Ministry of Education, Northeast Electric Power University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10251073.pdf?arnumber=10251073

Reference43 articles.

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3. New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation

4. Time Series Shapelet Classification Based Online Short-Term Voltage Stability Assessment

5. Applied AI in instrumentation and measurement: The deep learning revolution

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