Intelligent integration of ANN and H‐infinity control for optimal enhanced performance of a wind generation unit linked to a power system

Abstract 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.