一个基于微电网深度神经网络的新型电压控制系统,包括通信延迟作为一个复杂的大规模系统
1Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
ISA transactions
|January 23, 2025
概括
一个新的软开关电压控制系统有效地管理广泛的微电网与通信延迟. 这种深度神经网络方法增强了稳定性,而传统方法在动态条件下失败.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 可再生能源系统可再生能源系统
背景情况:
- 微电网对于电网稳定和可持续能源发展至关重要.
- 快速扩张的微电网需要解决电源质量,双向流量和电压/频率稳定等控制挑战.
- 传感器数据传输的通信延迟是一个重大挑战,特别是在大型复杂的微电网中.
研究的目的:
- 为广泛的微电网提出一种新的软切换电压控制系统.
- 在存在时间变化的通信延迟的情况下解决电压控制问题.
- 在33个总线微电网模型上评估系统的性能.
主要方法:
- 软切换控制系统的开发,集成静态输出反控制器和深度神经网络.
- 在33个总线微电网上实现和模拟,这是一个代表性的大规模系统.
- 在动态,时间变化的通信延迟下分析控制系统性能.
主要成果:
- 拟议的软开关控制器在动态通信延迟的情况下证明了在管理电压控制方面的有效性.
- 没有软切换的静态输出反控制器足以应对大型微电网中的静态通信延迟.
- 该研究验证了控制器在复杂场景中保持稳定性和性能的能力.
结论:
- 新型软开关电压控制系统为面临通信延迟的广泛微电网提供了强大的解决方案.
- 深度神经网络与静态输出反控制器相结合,在具有挑战性的条件下增强了微电网控制.
- 这项研究有助于开发更具弹性和高效的绿色能源基础设施.
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