Abstract
In this paper, a recompression S-CO2 Brayton cycle model that considers the finite-tem-perature difference heat transfer between the heat source and the working fluid, irreversible com-pression, expansion, and other irreversibility is established. First, the ecological function is ana-lyzed. Then the mass flow rate, pressure ratio, diversion coefficient, and the heat conductance distribution ratios (HCDRs) of four heat exchangers (HEXs) are chosen as variables to optimize cycle performance, and the problem of long optimization time is solved by building a neural network prediction model. The results show that when the mass flow rate is small, the pressure ratio, the HCDRs of heater, and high temperature regenerator are the main influencing factors of the ecological function; when the mass flow rate is large, the influences of the re-compressor, the HCDRs of low temperature regenerator, and cooler on the ecological function increase; reasonable adjustment of the HCDRs of four HEXs can make the cycle performance better, but mass flow rate plays a more important role; the ecological function can be increased by 12.13%, 31.52%, 52.2%, 93.26%, and 96.99% compared with the initial design point after one-, two-, three-, four-and five-time optimiza-tions, respectively.
Author supplied keywords
Cite
CITATION STYLE
Jin, Q., Xia, S., & Xie, T. (2022). Ecological Function Analysis and Optimization of a Recompression S-CO2 Cycle for Gas Turbine Waste Heat Recovery. Entropy, 24(5). https://doi.org/10.3390/e24050732
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.