智能电网逆变器控制:集成RNN,模型预测和自适应的滑动模式控制器,以实现最佳的波缓解
Omar Zeb1, Atif Rehman2, Nadia Sultan3
1School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Scientific reports
|March 17, 2026
概括
本研究介绍了连接到电网的电压源逆变器的混合控制系统,提高了智能电网的稳定性和效率. 这种新的方法显著减少了波扭曲,并在具有挑战性的电网条件下改善了动态响应.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 电力电子 电力电子 电力电子
背景情况:
- 连接到电网的电压源逆变器 (GC-VSI) 面临着波扭曲和电网不稳定等挑战.
- 传统模型预测控制 (MPC) 准确但计算密集;反复神经网络 (RNN) 快速但缺乏正式的控制保证.
研究的目的:
- 为GC-VSI开发一个强大且计算效率高的混合控制策略.
- 解决智能电网中的波,电网波动和外部干扰等问题.
主要方法:
- 一种混合控制,结合了离线MPC轨迹优化,实时RNN实现和自适应屏障条件超扭曲滑动模式控制器 (ABC-STSMC).
- 用MPC数据训练RNN,以减少在线计算负载.
- 稳定性和误差极限的利亚普诺夫分析.
- 改进了灰狼优化 (IGWO) 用于参数调整.
主要成果:
- 与独立的MPC和RNN控制器相比,混合ABC-STSMC显示出优异的波减弱和动态响应.
- 在弱电网,不平衡负载和扭曲电压条件下实现最小的总波扭曲 (THD).
- 通过广泛的模拟和Hardware-in-the-Loop实验进行验证.
结论:
- 拟议的混合控制系统为智能电网中先进的GC-VSI控制提供了计算效率高和强大的解决方案.
- 在非线性和不确定的电网环境中有效提高稳定性和性能.
- 在管理复杂的逆变器控制挑战方面取得了重大进展.
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