Design of an Adaptive PID Controller Based Linear Neural Network for Two-Area Interconnected Power System

The automatic load frequency control for multi-area power systems has presented a significant challenge for power system engineers since It requires to design a robust controller for maintaining the balance between the generation and consumption of electricity within each area, as well as the entire power grid. This study focuses on the load-frequency control of an interconnected two-area power system, aiming to minimize the area control error through adaptive control method. Specifically, an adaptive linear neural network known as ADALINE is employed to dynamically adjust the parameters of a PID controller in real-time. This approach effectively governs both the frequency deviation and tie-line power flow deviation at the interconnection point. The outcomes of the study revealed that the employing of the adaptive LNN-PID controller results in reduced frequency deviations, small overshoots and minimal oscillations. Furthermore, the power system demonstrated more robustness against wide range of operational conditions, even when faced with significant load changes and system uncertainties. These findings underscore the effectiveness of intelligent control strategies in optimizing the performance of interconnected power systems.