SFR Modeling for Hybrid Power Systems Based on Deep Transfer Learning-Reference-Cited by-同舟云学术

SFR Modeling for Hybrid Power Systems Based on Deep Transfer Learning

Author:

Zhang Jianhua¹^ORCID,Wang Yongyue¹,Li Hongrui²,Zhou Guiping³,Li Bin³,Wang Lei³,Li Kang⁴^ORCID

Affiliation:

1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China

2. North China Electric Power University, Beijing, China

3. State Grid Liaoning Electric Power Supply Company, Ltd., Shenyang, China

4. School of Electronic and Electrical Engineering, University of Leeds, Leeds, U.K.

Funder

National Key R&D Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

Reference38 articles.

2. A wide-area measurement data based method for power system dynamic frequency analysis;Liu;Power Syst. Technol.,2013

3. Minimum frequency prediction of power system after disturbance based on the WAMS data;Liu,2014

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