Increasing the penetration of Renewable Energy Sources (RES) into power systems created challenges and difficulties in the management of power flow since RES have variable power production based on their sources, such as Wind Turbines (WT), which depend on the wind speed. This article used Optimal Power Flow (OPF) to reduce these difficulties and to explain how the OPF can manage the power flow over the system, taking different cases of WT power production based on the different wind speeds. It also used Fixable AC Transmission (FACT) devices such as Thyristor-Controlled Series Compensators (TCSC) to add features to the controllability of the power system. The OPF is a non-linear optimization problem. To solve this problem, the artificial intelligence optimization technique is used. Particle Swarm Optimization (PSO) has been used in the OPF problem in this article. The Objective Functions O.F. discussed here are losses (MW), Voltage Deviation VD (p.u.), and thermal generation fuel Cost ($/h). This article used the wind turbine bus magnitude voltage and the reactance of TCSC as a control variable in OPF. To test this approach, the IEEE 30 bus system is used.
This work focuses on the use of the Linear Quadratic Gaussian (LQG) technique to construct a reliable Static VAr Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), and Excitation System controller for damping Subsynchronous Resonance ( SSR ) in a power system. There is only one quantifiable feedback signal used by the controller (generator speed deviation). It is also possible to purchase this controller in a reduced-order form. The findings of the robust control are contrasted with those of the "idealistic" full state optimal control. The LQG damping controller's regulator robustness is then strengthened by the application of Loop Transfer Recovery (LTR). Nonlinear power system simulation is used to confirm the resilience of the planned controller and demonstrates how well the regulator dampens power system oscillations. The approach dampens all torsional oscillatory modes quickly while maintaining appropriate control actions, according to simulation results.