一种适应模型预测控制方法,用于在可再生能源干扰下强大的负载频率控制
Mohamed Ayman1, Mahmoud A Attia2, Ahmed M Asim1
1Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Scientific reports
|January 16, 2026
概括
本研究介绍了一种适应模型预测控制 (AMPC) 用于电力系统中强大的负载频率控制 (LFC). 该AMPC战略显著提高了系统稳定性和性能,在各种电网条件下表现优于传统控制器.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 电力系统 电力系统
背景情况:
- 负载频率控制 (LFC) 对于保持电力系统稳定性至关重要.
- 传统的控制器在参数不确定性和可再生能源整合方面扎.
- 具有高可再生能源透率的低惯性电网带来了重大的LFC挑战.
研究的目的:
- 开发和验证适应模型预测控制 (AMPC) 战略,以实现强大的LFC.
- 增强实时模型适应和电力系统的约束意识预测调节.
- 为了证明AMPC在动态和不确定的环境中优于现有控制方法的优势.
主要方法:
- 整合在线系统识别使用递归最小方程 (RLS).
- 实施一个回落地平线优化框架用于预测控制.
- 在各种干扰下对单面积和双面积电力系统的模拟研究.
主要成果:
- 与PI/PID (20-40秒) 相比,AMPC实现了显著更快的沉时间 (0.5-2秒).
- 在AMPC中观察到消除过剩和大幅减少不足.
- 在动态和可再生能源干扰下,AMPC在减轻偏差方面表现卓越.
结论:
- 拟议的AMPC战略为现代电力系统中的LFC提供了一个强大而有效的解决方案.
- 对于低惯性电网,AMPC被证明是可扩展的,优于传统和优化的控制器.
- 控制器的适应性确保在负载变化和可再生能源集成中可靠的性能.
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