Predicting Failure Cascades in Large Scale Power Systems via the Influence Model Framework-Reference-Cited by-同舟云学术

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Predicting Failure Cascades in Large Scale Power Systems via the Influence Model Framework

Published:2021-09 Issue:5 Volume:36 Page:4778-4790
ISSN:0885-8950
Container-title:IEEE Transactions on Power Systems
language:
Short-container-title:IEEE Trans. Power Syst.

Author:

Wu Xinyu^ORCID,Wu Dan^ORCID,Modiano Eytan

Funder

Defense Threat Reduction Agency

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

https://ieeexplore.ieee.org/ielam/59/9519130/9384281-aam.pdf

Cited by 19 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. Mitigating cascading failure in power grids with deep reinforcement learning-based remedial actions;Reliability Engineering & System Safety;2024-10

2. Identifying the dominant operating variables to evaluate the cascading failure potential in the power system by theory of mutual information;International Journal of Electrical Power & Energy Systems;2024-10

3. Predicting Cascading Failures with a Hyperparametric Diffusion Model;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. Machine learning applications in cascading failure analysis in power systems: A review;Electric Power Systems Research;2024-07

5. Distributed Observer-Based Failure Compensation Load Frequency Control of Multi-Area Power Systems;2024 3rd Conference on Fully Actuated System Theory and Applications (FASTA);2024-05-10

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