Adaptive Neuro-Fuzzy Fractional Load Frequency Control via Neural Network Observer

A novel load frequency control (LFC) in microgrids through the integration of a Fractional Order Proportional-Integral-Derivative (FOPID) controller with an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed in this paper. To improve disturbance rejection capabilities, a Radial Basis Function (RBF) disturbance observer is incorporated into the proposed system. The Geometric Mean Optimizer algorithm is utilized in order to efficiently optimize the controller’s parameters. In order to evaluate the proposed method’s performance in addition to the Load demand, wind power and Photovoltaic (PV) power perturbations also an external disturbance is applied to the system. The proposed method’s performance was compared to conventional methods through several different scenarios. The simulations were done in MATLAB/Simulink 2021b.