In this paper, an innovative load frequency control (LFC) method is proposed, enhancing the strengths and addressing the weaknesses of previous methods. The proposed LFC method is an adaptive controller based on interval type‐2 fuzzy logic, optimally designed using novel objective function and an enhanced version of the bald eagle search (BES) algorithm with coefficients optimally determined by the lightning search algorithm (LSA) called the hybrid BES and LSA (hBES‐LSA). Also, a detailed power system model incorporating renewable solar and wind farms for conducting LFC studies, accounting for uncertainties in wind speed, solar radiation, and power transmission line parameters using probability density functions and Monte Carlo simulation (MCS) is presented. The paper presents simulation results obtained in MATLAB, divided into three parts. The first part validates the proposed hBES‐LSA accuracy through optimization of standard benchmark functions ZDF. Here, hBES‐LSA achieves the lowest mean and standard deviation compared to other algorithms across 10 chosen ZDF objective functions. The second part investigates the impact of environmental changes on tie‐line parameters. The simulations reveal that these parameters can fluctuate up to 20% due to weather variations and operational changes. Finally, the third part assesses the proposed LFC method’s performance in controlling two‐area and three‐area power systems frequency compared to existing methods. The simulations highlight the significant influence of uncertainties on LFC controller performance, leading to increased frequency oscillations and damping times. However, the proposed adaptive control method demonstrates superior frequency stabilization compared to other approaches.
Mohammadi et al. (Thu,) studied this question.