  Control of non-condensing non-ideal-gas power cycles is challenging because
their output power dynamics depend on complex system interactions,
non-ideal-gas effects complicate turbomachinery behavior, and state constraints
must be respected. This article presents a control methodology for these
systems, comprising a control modeling approach and model predictive control
(MPC) strategy. This methodology is demonstrated on the high-pressure side of a
simple supercritical CO2 cycle power block, composed of a variable-speed
compressor, heat exchanger, and fixed-speed turbine. The control model is
developed by applying timescale-separation arguments to a high-fidelity
simulation model and locally linearizing non-ideal-gas turbomachinery
performance maps. MPC is implemented by linearizing the control model online at
each sampling instant. Closed-loop simulations with a full-order gas-dynamics
truth model demonstrate the effectiveness of the proposed control methodology.
In response to load changes, the controller maintains high turbine inlet
temperatures while achieving net power output ramp rates in excess of 100% of
nameplate output per minute. The controller often acts at the intersection of
motor torque, compressor surge, and turbine inlet temperature constraints, and
performs well from 35 to 105% of nameplate capacity with no parameter
scheduling. Good performance and fast update rates are obtained via online
linearization. The results demonstrate the suitability of MPC for the
supercritical CO2 cycle, and the proposed methodology is extensible to more
complex cycle variants such as the recuperated and recompression cycle.
