A Neural Lyapunov Approach to Transient Stability Assessment in Interconnected Microgrids

Date
2021-01-05
Authors
Huang, Tong
Gao, Sicun
Long, Xun
Xie, Le
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
We propose a neural Lyapunov approach to assessing transient stability in power electronic-interfaced microgrid interconnections. The problem of transient stability assessment is cast as one of learning a neural network-structured Lyapunov function in the state space. Based on the function learned, a security region is estimated for monitoring the security of interconnected microgrids in real-time operation. The efficacy of the approach is tested and validated in a grid-connected microgrid and a three-microgrid interconnection. A comparison study suggests that the proposed method can achieve a less conservative characterization of the security region, as compared with a conventional approach.
Description
Keywords
Resilient Networks, interconnected microgrids, machine learning, neural lyapunov approach, power grid resilience, transient stability
Citation
Rights
Access Rights
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.