Data-driven modeling of power system dynamics: Challenges, state of the art, and future work-Reference-Cited by-同舟云学术

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Data-driven modeling of power system dynamics: Challenges, state of the art, and future work

Published:2023-09 Issue:3 Volume:2 Page:200-221
ISSN:2771-9197
Container-title:iEnergy
language:
Short-container-title:iEnergy

Author:

Huang Heqing¹,Lin Yuzhang¹,Zhou Yifan²,Zhao Yue²,Zhang Peng²,Fan Lingling³

Affiliation:

1. University of Massachusetts Lowell,Department of Electrical and Computer Engineering,Lowell,MA,USA,01852

2. Stony Brook University,Department of Electrical and Computer Engineering,Stony Brook,NY,USA,11794

3. University of South Florida,Department of Electrical and Computer Engineering,Tampa,FL,USA,33620

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9732629/10304822/10304823.pdf?arnumber=10304823

Reference176 articles.

1. Power system load modeling by learning based on system measurements

2. Dynamic reactive load model

3. Dynamic load models in power systems using the measurement approach

4. Measurement-Based Load Modeling Using Transfer Functions for Dynamic Simulations

5. Measurement-Based Dynamic Load Models: Derivation, Comparison, and Validation

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Aggregated and Reduced-Order Admittance-Based Modeling of Converter-Interfaced Resources for Power Systems Transient Analysis;2024 6th Global Power, Energy and Communication Conference (GPECOM);2024-06-04

2. Hybrid CNN-LSTM Network for Time-Varying Wide-area Composite Load Model Parameter Identification in Power Systems;2024 6th Asia Energy and Electrical Engineering Symposium (AEEES);2024-03-28

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