Multistage Turbomachinery Optimization for High-Temperature Heat Pumps With the Reverse Rankine Cycle

Abstract

The electrification of process heat generation will be a key to achieving carbon neutrality in the coming decades. One of the most promising approaches is to replace conventional heat supply systems with high-temperature heat pumps (HTHPs). A promising heat pump concept is based on the reverse Rankine cycle that uses water as its working fluid. By using turbomachinery for the compression process in this cycle, the performance of the HTHP can be increased compared to the volumetric displacement systems, like screw or piston compressors. Although the design of the compressor geometry can be done sequentially in relation to the HTHP cycle design, better results can be obtained by an approach that integrates turbomachinery and the thermodynamic cycle design. Against this background, an automated optimization method for a reverse Rankine HTHP with two radial turbo-compressors in series is presented. In contrast to the current state of the art, the presented novel optimization approach uses 3D computational fluid dynamics data to calculate the compressor’s performance. Furthermore, the integration of low-fidelity compressor specific reduced-order models are used to accelerate the gradient-free optimization process by a CO-Kriging surrogate model. The advantages of the novel approach are justified by comparing the numerical effort and the final values of the optimization objectives.