Data‐driven transient frequency stability assessment: A deep learning method with combined estimation‐correction framework-Reference-Cited by-同舟云学术

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Data‐driven transient frequency stability assessment: A deep learning method with combined estimation‐correction framework

Published:2020-11-03 Issue:3 Volume:1 Page:198-209
ISSN:2634-1581
Container-title:Energy Conversion and Economics
language:en
Short-container-title:Energy Conversion and Economics

Author:

Wen Yunfeng¹,Zhao Rongzhen²,Huang Mingzeng¹,Guo Chuangxin³

Affiliation:

1. College of Electrical and Information Engineering Hunan University Changsha Hunan Province China

2. Nanjing NR Electric Co. Ltd. Nanjing Jiangsu Province China

3. College of Electrical Engineering Zhejiang University Hangzhou Zhejiang Province China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/enc2.12015

Reference27 articles.

1. Modeling Load Dynamics to Support Resiliency-Based Operations in Low-Inertia Microgrids

2. Enhancing Frequency Stability of Asynchronous Grids Interconnected with HVDC Links

3. Hybrid renewable energy systems for power generation in stand-alone applications: A review

4. Frequency stability for an island power system: Developing an intelligent preventive‐corrective control mechanism for an offshore location;Wu Y.K.;IEEE Industry Appl. Mag.,2017

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3. Coordinated restoration of inverter‐based power sources and synchronous generators for the high renewable penetrated power system considering the dynamic frequency regulation capability;IET Renewable Power Generation;2024-01-23

4. Review on measurement-based frequency dynamics monitoring and analyzing in renewable energy dominated power systems;International Journal of Electrical Power & Energy Systems;2024-01

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