A Neural Lyapunov Approach to Transient Stability Assessment in Interconnected Microgrids

Conference · Tue Jan 05 04:00:00 EST 2021

OSTI ID:2427387

Huang, Tong; Gao, Sicun; Long, Xun; Xie, Le

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.

• Research Organization: Texas A&M Engineering Experiment Station
• Sponsoring Organization: USDOE
• DOE Contract Number: EE0009031
• OSTI ID: 2427387
• Country of Publication: United States
• Language: English