Two Separate Continually Online-Trained Neurocontrollers for a Unified Power Flow Controller
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Abstract
The crucial factor affecting the modern power systems today is load flow control. The Unified Power Flow Controller (UPFC) provides an effective means for controlling the power flow and improving the transient stability in a power network. The UPFC has fast complex dynamics and its conventional control is based on a linearized model of the power system. This paper presents the design of neurocontrollers to provide better damping during transient and dynamic control. Two separate neurocontrollers are used for controlling the UPFC, one neurocontroller for the shunt inverter and the other for the series inverter. Simulation studies carried out in the PSCAD/EMTDC environment is described and results show the successful control of the UPFC and the power system with two neurocontrollers. Performances of the neurocontrollers are compared with the conventional proportional plus integral controllers for system oscillation damping under different operating conditions for large disturbances.
