Minimum inertia demand estimation of new power system considering diverse inertial resources based on deep neural network-Reference-Cited by-同舟云学术

Minimum inertia demand estimation of new power system considering diverse inertial resources based on deep neural network

Published:2022-12-05 Issue:1 Volume:5 Page:80-94
ISSN:2516-8401
Container-title:IET Energy Systems Integration
language:en
Short-container-title:IET Energy Syst Integration

Author:

Zicheng Liu¹^ORCID,Zhou Tao¹,Chen Zhong²,Wang Yi³,Wang Yalun¹

Affiliation:

1. School of Automation Nanjing University of Science and Technology Nanjing China

2. School of Electrical Engineering Southeast University Nanjing China

3. State Grid Electric Power Research Institute Smart Grid Protection and Operation Control National Key Laboratory Nanjing China

Funder

Natural Science Foundation of Jiangsu Province

Publisher

Institution of Engineering and Technology (IET)

Subject

Energy Engineering and Power Technology,Engineering (miscellaneous),Renewable Energy, Sustainability and the Environment,Environmental Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/esi2.12086

Reference30 articles.

1. Multi‐dimensional assessment of the inertia level of power systems with high penetration of HVDCs and Renewables;Xiao Y.;Electr. Power Construct.,2020

2. On-Line Inertia Estimation for Synchronous and Non-Synchronous Devices

3. Smart frequency control in low inertia energy systems based on frequency response techniques: A review

4. Switching Markov Gaussian Models for Dynamic Power System Inertia Estimation

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