Robust GPC Using Neural Networks for Phase-Shifting Transformers to Compensate Powers in a Transmission Line

The usage of electricity is steadily rising, and this pattern will last in the future. Fast network control systems have also been recently investigated and created, and some are already in regular use, while others are in pilot applications or are prototypes. This paper aims to demonstrate that these systems, also known as FACTS (Flexible Alternative Current Transmission Systems), have similarly dethroned traditional systems while offering better solutions and resolving the issue of energy quality, similar to the hybrid system, which opens up new opportunities for more effective network utilization through continuous and quick action on the various network parameters (voltage, phase shift, and impedance); consequently, the power transits will be more efficient. While ensuring robust control with cutting-edge algorithms through the creation of identification/control strategies based on GPC neural network and generalized predictive control.