基于虚拟惯性调节的弱微电网的高阶观察员,使用深度序列学习
Shuguang Li1, Shupeng Song1, Mai The Vu2
1School of Computer Science and Technology, Shandong Technology and Business University, Yantai 264005, China.
ISA transactions
|October 12, 2025
概括
这项研究通过使用自适应性虚拟频率控制器来增强具有可持续能源的低惯性混合微电网. 这种新方法改善了系统惯性和减压,在动态稳定性方面表现优于传统方法.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 整合可再生能源的整合
背景情况:
- 在混合微电网系统 (HMGS) 中,可持续能源资源 (SER) 的高透率减少了由于电力电子接口的惯性.
- 在HMGS的低惯性导致频率不稳定性和电网管理的挑战.
研究的目的:
- 在低惯性HMGS中引入适应性虚拟频率控制器 (VFC) 用于能量存储系统 (ESS).
- 为了提高HMGS的动态稳定性和响应能力,具有高的SER透率.
主要方法:
- 实施高级扩展干扰观察员 (HOEDO) 进行干扰估计和补偿.
- 应用深度顺序动作值学习 (SAVL) 进行无监督的控制器参数调整.
- 在控制循环中模拟虚拟转子动态,以提高响应性.
主要成果:
- 可适应的VFC有效地改善了系统惯性和减压特性.
- 与传统的虚拟惯性控制方法相比,拟议的方案显示出更高的性能.
- 控制器在不同的条件下表现出更快的动态响应和抑制波动.
结论:
- 使用HOEDO和深度SAVL的自适应VFC为稳定低惯性HMGS提供了强大的解决方案.
- 这种方法提高了电网的弹性,并促进了SERs的更高的整合.
- 该方法对微电网稳定性的现有控制策略提供了显著的进步.
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