Neuroidentification of System Parameters for the Shunt & Series Branch Control of UPFC

Ganesh K. Venayagamoorthy, Missouri University of Science and Technology
Radha P. Kalyani
Mariesa Crow, Missouri University of Science and Technology

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/1774

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Abstract

The crucial factor affecting the modern power systems today is load flow control. The unified power flow controller (UPFC) forms an affective means for controlling the power flow. The UPFC consists of shunt and series inverters which are conventionally controlled using linear controllers. This paper presents the design of neuroidentifiers that identify the system parameters that determine the UPFC controller outputs one-time step ahead thus, making the pathway for the design of adaptive neurocontrollers. Two neuroidentifiers are used for identifying the nonlinear dynamics of power system and UPFC, one neuroidentifier for the shunt inverter and the other for the series inverter. Simulation results carried out in the PSCAD/EMTDC environment are presented to show the successful neuroidentification of system parameters are possible.