The crucial factor affecting the modern power systems today is load flow 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 neuroidentifiers that models the system dynamics one-time step ahead making the pathway for the design of adaptive neurocontrollers. Two neuroidentifiers are used for identifying the nonlinear dynamics of a multimachine power system and UPFC, one neuroidentifier 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 neuroidentification of system dynamics.
R. P. Kalyani and G. K. Venayagamoorthy, "Neuroidentification of System Parameters of the UPFC in a Multimachine Power System," Proceedings of International Conference on Intelligent Sensing and Information Processing, 2004, Institute of Electrical and Electronics Engineers (IEEE), Jan 2004.
The definitive version is available at https://doi.org/10.1109/ICISIP.2004.1287660
International Conference on Intelligent Sensing and Information Processing, 2004
Electrical and Computer Engineering
Keywords and Phrases
PI Control; PI Controllers; Adaptive Control; Adaptive Neurocontrollers Design; Control System Synthesis; Invertors; Load Flow Control; Multimachine Power System; Neurocontrollers; Neuroidentification; Neuroidentifiers; Nonlinear Dynamics; Parameter Estimation; Parameter Identification; Power System CAD; Power System Control; Series Inverter; Shunt Inverter; System Dynamics; System Parameters; Unified Power Flow Controller
Article - Conference proceedings
© 2004 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.