Universal phase shifter regulator system modeling with robust GPC using neural networks for compensation power in transmission line

Abstract

Electricity consumption is increasing gradually and this trend will continue in the future. In addition, rapid network control systems using the resources offered by power electronics and control microelectronics have been recently studied and developed, and are currently in normal application for some, for others, in pilot applications or as prototypes. This paper attempts to show that these systems are referred to by the general acronym flexible alternative current transmission systems (FACTS) similarly dethroned the traditional systems while offering better solutions and solving the energy quality problem such as the hybrid system (unified power flow controller (UPFC), or universal phase shifter regulator (UPSR)) which opens up new perspectives for more efficient operation of networks by continuous and rapid action on the various parameters of the network (voltage, phase shift, and impedance); thus, the power transits will be better controlled and the voltages better held, which will make it possible to increase the stability margins or tend towards the thermal limits of the lines. In this work, we used a classic control (PI-decoupled) and others while offering more flexibility of control thanks to the development of strategies identification/control based on generalized predictive control (GPC) with neural network to ensure robust control with advanced algorithms.