The ITER Pulsed Power Electrical Network (PPEN) supplies the superconducting magnets and the Heating and Current Drive systems. During the experimental pulses, about several hundreds of seconds long, active power consumption of 500 MW and reactive one of 950 Mvar are foreseen. The ITER power supply system is very large and complex and a careful design is required to assure a safe operation. Stability of ITER PPEN has been already investigated in recent studies by numerical simulation and analytical methods. Now a new dynamic analytical model of the ITER power supply system is being developed, based on the state space theoretical approach, which allows the application of the linear control theory to study the stability of the whole system. For each subsystem of the ITER power supply a state space model has been developed, and in this paper the ac/dc converter model is presented and validated.

Continuous State Space Model of the ITER ac/dc converters for stability analysis of the Pulsed Power Electrical Network

Gaio E;
2015

Abstract

The ITER Pulsed Power Electrical Network (PPEN) supplies the superconducting magnets and the Heating and Current Drive systems. During the experimental pulses, about several hundreds of seconds long, active power consumption of 500 MW and reactive one of 950 Mvar are foreseen. The ITER power supply system is very large and complex and a careful design is required to assure a safe operation. Stability of ITER PPEN has been already investigated in recent studies by numerical simulation and analytical methods. Now a new dynamic analytical model of the ITER power supply system is being developed, based on the state space theoretical approach, which allows the application of the linear control theory to study the stability of the whole system. For each subsystem of the ITER power supply a state space model has been developed, and in this paper the ac/dc converter model is presented and validated.
2015
Istituto gas ionizzati - IGI - Sede Padova
9781479982646
ITER power supply
state space model
eigenvalue analysis
frequency analysis
st ability analysis
small signal analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/324763
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