Deep learning based on Transformer architecture for power system short-term voltage stability assessment with class imbalance

no code implementations • 18 Oct 2023 • Yang Li, Jiting Cao, Yan Xu, Lipeng Zhu, Zhao Yang Dong

This work proposes a Transformer-based STVSA method to address this challenge.

Clustering Generative Adversarial Network +1

PMU measurements based short-term voltage stability assessment of power systems via deep transfer learning

no code implementations • 7 Aug 2023 • Yang Li, Shitu Zhang, Yuanzheng Li, Jiting Cao, Shuyue Jia

Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems.

Data Augmentation Transfer Learning

A review of data-driven short-term voltage stability assessment of power systems: Concept, principle, and challenges

no code implementations • 22 Dec 2021 • Jiting Cao, Meng Zhang, Yang Li

With the rapid growth of power market reform and power demand, the power transmission capacity of a power grid is approaching its limit, and the secure and stable operation of power systems becomes increasingly important.