| |
LSTM Data-Driven Model of Multi-scene Virtual Synchronous Generator
| [View]
[Download]
|
| Author(s) |
Jiangbin TIAN, Jinbin ZHAO, Guohui ZENG, Xiangchen ZHU, Zhenhua ZHANG, Yuzong WANG |
| Abstract |
This paper proposes a data-driven modeling approach using LSTM to accurately describe the dynamic characteristics of Virtual Synchronous Generator (VSG) systems. VSG technology allows grid-connected inverters to resemble synchronous generators externally. However, the commonly used small-signal model faces challenges in capturing the complexity of VSG systems, particularly in complex scenarios. The proposed LSTM-based data-driven model considers the impact of irrational factors, providing accurate and stable VSG system modeling. Experimental results demonstrate the superiority of the LSTM neural network-based data-driven VSG model over the small-signal model and typical data-driven models in terms of accuracy and stability. |
| Download |
| Filename: | 0038-epe2023-full-15273815.pdf |
| Filesize: | 1.604 MB |
|
| Type |
Members Only |
| Date |
Last modified 2023-09-24 by System |
| |
 |