P–Q decoupled control schemes using fuzzy neural networks for the unified power flow controller

This paper presents a new P–Q decoupled control scheme using fuzzy neural networks for the unified power flow controller (UPFC) to improve the dynamic control performance of power systems with the aim of reducing the inevitable interactions between the real and reactive power flow control parameters. In this paper, a set of equivalent controlled current and voltage sources is adopted for mathematically modeling the UPFC and the test power systems. To simplify the theoretical analysis of the control system the 3-phase description of a two-bus test power system model embedded with a UPFC is transformed into d–q components based on a synchronously rotating reference frame. For the control systems with inherent nonlinear coupling features, a feed-forward control scheme based on fuzzy neural controllers is developed to realize the decoupling control objectives. Based on the simulation results, the proposed control scheme is able to overcome the drawbacks of the traditional power flow controllers on small disturbance linearizing method. Comprehensive simulation results on the PSCAD and MATLAB programs are presented and discussed to verify the effectiveness of the proposed control scheme.