Neuroidentification of system parameters of the upfc in a multimachine power system

Abstract

The crucial factor affecting the modern power systems today is loadflow control. The Unified Power Flow Controller is an effective means for controlling the power flow. The UPFC is controlled conventionally using PI Controllers. This paper presents the designs of neuroidentiJiers that models the system dynamics one-time step ahead making the pathway for the design of adaptive neurocontrollers. Two neuroidentiJiers are used for identifjling the nonlinear dynamics of a multimachine power system and UPFC, one neuroidentifer for the shunt inverter and another for the series inverter. Simulation results carried out in the PSCAD/EMTDC environments on multimachine power system are presented to show the successful neuroidentifcation of system dynamics.