A DIRECT CONTROL SCHEME BASED ON RECURRENT FUZZY NEURAL NETWORKS FOR THE UPFC SERIES BRANCH

`In this paper, a new control scheme using recurrent fuzzy neural controllers is proposed for the series branch of the unified power flow controller (UPFC) to improve the dynamic performance of real-time power flow control functions with the aim of reducing the inevitable interaction between the real and reactive power flow control parameters. To simplify the theoretical analysis of the coupled dynamics within the UPFC and the controlled power system, the three phase description of a two-bus test power system embedded with a UPFC is transformed into d - q components based on a synchronously rotating reference frame. For 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 designed on small disturbance linearizing methods. Comprehensive simulation results on the EMTDC/PSCAD and MATLAB programs are presented and discussed to verify the effectiveness of the proposed control scheme.