Improving Frequency Control Strategy of Interconnected Power Systems with Renewable Energy Integration Using an Adaptive Neuro-Fuzzy Inference System Controller

Maintaining frequency stability within a power system can be a critical criterion for ensuring reliable and secure grid operation. This challenge is particularly pronounced in today's wide-ranging and interconnected systems, where the presence of non-linear properties and the increasing integration of renewable energy sources introduce significant complexities. This work is a new approach to using an Adaptive Neuro-Fuzzy Inference System (ANFIS) methodology to achieve robust frequency control in such environments. The proposed approach is evaluated within a three-area interconnected power system model incorporating diverse turbine types, Governor Dead-Band (GDB), Generation Rate Constraint (GRC), and renewable energy sources. The effectiveness of the ANFIS controller is subsequently validated through comparative analysis with existing control strategies, as evidenced by the superior performance demonstrated in numerical simulation results.