Model-based Optimal Scenario Planning in EAST
H. Wang, E. Schuster, T. Rafiq, A. Kritz, S. Ding
Fusion Engineering and Design, 123 (2017) 569–573
Abstract
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Ongoing work in the fusion community focuses on developing advanced
plasma scenarios characterized by high plasma confinement,
magnetohydrodynamic (MHD) stability, and noninductively driven plasma
current. The toroidal current density profile, or alternatively the q
profile, together with the normalized beta, are often used to
characterize these advanced scenarios. The development of these advanced
scenarios is experimentally carried out by specifying the devices’
actuator trajectory waveforms, such as the total plasma current, the
plasma density, and the auxiliary heating and current-drive (H&CD)
sources based on trial-and-error basis. In this work, a model-based
numerical optimization approach is followed to complement the
experimental effort on actuator trajectory planning in the EAST tokamak.
The evo- lution of the q profile is closely related to the evolution
of the poloidal magnetic flux profile, whose dynamics is modeled by a
nonlinear partial differential equation (PDE) referred to as the
magnetic-flux diffusion equation (MDE). In this work, the MDE is
combined with physics-based correlations obtained from EAST experimental
data for the plasma density, temperature, resistivity and non-inductive
current drives to develop a control-oriented nonlinear PDE model. The
optimization objective is to design feed- forward trajectories for the
plasma current, plasma density, electron cyclotron heating power,
neutral beam injection power and lower hybrid current drive power that
steer the plasma to desired q profile and normalized beta such that the achieved state
is stationary in time. The optimization is subject to the plasma dynamics
(described by the physics-based PDE model) and plasma state and actuator
constraints, such as the max- imum available amount of H&CD power and
MHD stability limits. This defines a nonlinear, constrained optimization
problem that is solved by employing sequential quadratic programming.
The optimized actuator trajectories are assessed in nonlinear transport
simulations in preparation for experimental tests in EAST.