智能集成 ANN 和 H-infinity 控制,优化提升与电力系统相连的风力发电机组的性能

Mohamed Abd‐El‐Hakeem Mohamed, Salah Kamel, Hamed Zeinoddini‐Meymand
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引用次数: 0

摘要

本文的重点是利用智能 H-∞ 综合法为通过静态 VAR 补偿器与电力系统相连的风力发电系统创建一个控制器。该控制方法有两个目的:一是增强系统对风力湍流变化的动态响应,二是提高发电质量。为了实现系统的最优控制,人工神经网络(ANN)与 H-∞ 控制方法相结合。人工神经网络擅长建模和优化,而 H-∞ 则优先考虑鲁棒性,以提高动态性能。将 ANN 和 H-∞ 相结合的控制策略能够提供卓越的性能、精确的跟踪和最小的过冲。这种方法能适应不断变化的控制信号,并表现出鲁棒性特征,能有效管理不确定性和干扰。通过模拟研究,与其他控制策略相比,该技术在增强系统动态响应方面的有效性得到了展示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent integration of ANN and H‐infinity control for optimal enhanced performance of a wind generation unit linked to a power system
This article focuses on utilizing intelligent H‐∞ synthesis to create a controller for a wind generation system linked to a power system via a static VAR compensator. The purpose of the control approach is twofold: firstly, to enhance the system's dynamic reactions to turbulent wind variations, and secondly, to elevate the quality of power generation. To achieve optimal control of the system, an Artificial Neural Network (ANN) is combined with the H‐∞ control method. This integration leverages the strengths of both ANN, which excels in modeling and optimization, and H‐∞, which prioritizes robustness to enhance dynamic performance. The resultant control strategy, connecting ANN and H‐∞, demonstrates the capability to deliver superior performance, precise tracking, and minimal overshooting. This approach is adaptive to changing control signals and exhibits robust characteristics, effectively managing uncertainties and disturbances. Through a simulation study, the effectiveness of this presented technique is showcased in enhancing the dynamic response of the system when compared to alternative control strategies.
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