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Deep-learning Based Modeling of Fault Detachment Stability for Power Grid

Machine Learning 2018-05-18 v1 Machine Learning

Abstract

The project intends to model the stability of power system with a deep learning algorithm to the problem, aiming to delay the removal of the fault. The so-called "fail-delay cut-off" refers to the occurrence of N-1 backup protection action on the backbone network of the system, resulting in longer time for the removal of the fault. In practice, through the analysis and calculation of a large number of online data, we have found that the N-1 failure system of the main protection action will not be unstable, which is also a guarantee of the operation mode arrangement. In the case of the N-1 backup protection action, there is an approximately 2.5% probability that the system will be destabilized. Therefore, research is needed to improve the operating arrangement.

Keywords

Cite

@article{arxiv.1805.06657,
  title  = {Deep-learning Based Modeling of Fault Detachment Stability for Power Grid},
  author = {Haotian Cui and Xianggen Liu and Yanhao Huang},
  journal= {arXiv preprint arXiv:1805.06657},
  year   = {2018}
}

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in Chinese

R2 v1 2026-06-23T01:58:27.225Z