Comparison of Intelligent Control Methods Performance in the UPFC Controllers Design for Power Flow Reference Tracking

Abstract

The Unified Power Flow Controller (UPFC) is one of such emerging FACTS devices that can manage the power flow in Transportation System. Based on the control system associated with the management of UPFC, both the controllers of shunt and series converters of UPFC are controlled conventionally using PIs controllers. However, the PI system alone cannot control the UPFC in the presence of uncertainty of system parameters and disturbances. For this reason, the use of novel robust techniques based on artificial intelligence theory in the design control of UPFC is very efficient for improving its performances. In this regard, four approaches have been used in this study to replace the conventional PI controller and enhance the performance of the UPFC for power flow reference tracking. In the first approach, the fuzzy logic technique (Mamdani and Sugeno types) has been employed to provide dynamic control of series and shunt converters of UPFC, whereas in the second method, the controllers of UPFC are performed through the optimization techniques such as: PSO, PSO_SQP, and GA techniques. The proposed techniques based UPFC are tested in MATLAB/Simulink software by using UPFC with a 48-pulse voltage source converter (VSC) equipping a High Voltage (HV) electrical network. In terms of dynamic performance, the simulations’ results and the comparative analysis clearly show the superiority of the intelligent controllers regardless of the variation of powers that affecting the model plant. Compared to PI controller, they ensure good performance in terms of tracking and decoupling.