Robust Controller Design for Delayed Load Frequency Control Systems Under Wind Power Uncertainty

Wind power uncertainty can significantly deteriorate the frequency regulation performance and robustness of load frequency control (LFC) systems, particularly in the presence of communication delays. However, most existing studies rely on simplified wind power fluctuation models, which cannot adequately capture the segmented and stochastic characteristics of wind speed variations. As a result, the resulting robustness analysis may deviate from practical operating conditions, leading to controller designs that are less reliable and less effective in real-world scenarios. To address this issue, this paper develops a robust controller co-design framework for delayed LFC systems under wind power uncertainty. First, a probabilistic wind power model with wind speed segmentation characteristics is established, and electric vehicles are incorporated into frequency regulation to construct a multi-area delayed LFC model. Then, a robust performance index is introduced to quantify disturbance rejection capability, and a genetic algorithm–particle swarm optimization-based collaborative optimization strategy is employed to determine controller parameters efficiently. Simulation results on both single-area and two-area LFC systems demonstrate that the proposed method achieves superior frequency regulation performance and stronger robustness against wind disturbances and time delays compared with designs that neglect wind uncertainty. Quantitatively, compared with controllers designed based on simplified wind power modeling, the proposed design framework reduces the normalized integral of time multiplied absolute value of the error (ITAE), integral of squared error (ISE), and integral of absolute error (IAE) indices by approximately 17.4% and 9% on average in the single-area and two-area cases, respectively.