Modeling of Extremely Short-Time Power Variations of Wound Rotor Induction Machines Wind Farms for Flicker Studies-Reference-Cited by-同舟云学术

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Modeling of Extremely Short-Time Power Variations of Wound Rotor Induction Machines Wind Farms for Flicker Studies

Published:2023 Issue: Volume:11 Page:135556-135567
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ketabipour Saeedeh¹,Samet Haidar¹^ORCID,Mohammadi Mohammad¹^ORCID,Li Qi²^ORCID,Terzija Vladimir³

Affiliation:

1. School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran

2. State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China

3. School of Engineering, Newcastle University, Newcastle upon Tyne, U.K

Funder

National Foreign Specialized Projects from the Chinese Ministry of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10332150.pdf?arnumber=10332150

Reference36 articles.

1. Short term wind speed forecasting for wind turbine applications using linear prediction method

2. Prediction of wind farm reactive power fast variations by adaptive one-dimensional convolutional neural network

3. Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

4. TS fuzzy prediction-based SVC compensation of wind farms flicker: A dual-UKF approach

5. Dynamic Behavior of a Class of Wind Turbine Generators During Randon Wind Fluctuations

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