Design and Computational Assessment of a Supercritical CO2 Compressor for Waste Heat Recovery Applications
The development of novel technical solutions for the effective recovery of waste heat is crucial for making accessible the enormous amount of thermal energy released by industrial processes, thus supporting the EU energy strategy. To this end, the EU-H2020 project CO2OLHEAT aims at developing, and demonstrating in a real industrial environment, a novel sCO2 power unit of 2-MW capacity recovering energy from flue gases at 400 °C. The thermo-economic optimization of the system and the complexity of its implementation led to select a simple recuperative cycle for the CO2OLHEAT unit, which features a relatively unconventional multi-shaft configuration where the sCO2 compressor is driven by a dedicated radial expander, while the electrical power is generated via a separated axial turbine.
The present study focused on the design and computational assessment of the compressor for the CO2OLHEAT system. The thermodynamic optimization of the cycle led to an overall pressure ratio slightly above 2.5, delivered with a two-stage centrifugal compressor. As typically found in sCO2 power systems, the thermodynamic state of the fluid at the machine intake (P = 85 bar; T = 32°C) is close to the critical point and to the saturation curve; therefore, the first stage of the machine demands a dedicated aero-thermodynamic design, which can account for the effects of non-ideal thermodynamics and of the potential onset of two-phase flows. The paper discusses the conceptual aero-mechanical design of the compressor and then focuses on its performance assessment over the full operating range via Computational Fluid Dynamics. Two alternative flow models are considered, the first one based on the experimentally-validated barotropic fluid representation, while the second one featuring a complete thermodynamic model which assumes homogeneous equilibrium between the phases. The approaches provide similar outcomes, showing that the compressor fulfills the system requirement and guarantees large rangeability.
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