TY - GEN
T1 - Design and Optimization of Multistage Axial-Flow Turbine for Compressed Air Energy Storage System
AU - Zhang, Shishu
AU - Hou, Yanshuo
AU - Hu, Zhongbo
AU - Jiang, Zhirong
AU - Shen, Wenting
AU - Zhang, Zhe
AU - Wang, Jiangfeng
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In compressed air energy storage systems, turbines play a critical role in energy recovery and improving overall system efficiency. To further enhance the aerodynamic performance of turbines and reduce carbon emissions, this study developed a one-dimensional design and optimization program for multistage axial-flow turbines. Based on the constructed one-dimensional aerodynamic framework, a genetic algorithm was integrated to achieve multi-objective optimization of isentropic efficiency and hub-tip ratio. After several iterations, the turbine's isentropic efficiency improved from 92.34% to 93.50%. Building upon the one-dimensional design, a three-dimensional model of the multistage axial turbine was established and verified through numerical simulations. The simulation result showed an efficiency of 93.25%, with a relative deviation of 0.27% compared to the one-dimensional design, further confirming the accuracy and feasibility of the optimization. The results demonstrate that this method can provide key technical support for the design of low-carbon energy storage equipment in compressed air energy storage systems.
AB - In compressed air energy storage systems, turbines play a critical role in energy recovery and improving overall system efficiency. To further enhance the aerodynamic performance of turbines and reduce carbon emissions, this study developed a one-dimensional design and optimization program for multistage axial-flow turbines. Based on the constructed one-dimensional aerodynamic framework, a genetic algorithm was integrated to achieve multi-objective optimization of isentropic efficiency and hub-tip ratio. After several iterations, the turbine's isentropic efficiency improved from 92.34% to 93.50%. Building upon the one-dimensional design, a three-dimensional model of the multistage axial turbine was established and verified through numerical simulations. The simulation result showed an efficiency of 93.25%, with a relative deviation of 0.27% compared to the one-dimensional design, further confirming the accuracy and feasibility of the optimization. The results demonstrate that this method can provide key technical support for the design of low-carbon energy storage equipment in compressed air energy storage systems.
KW - Compressed air energy storage system
KW - Genetic algorithm
KW - Multi-objective optimization
KW - Multistage axial-flow turbine
KW - Numerical simulation
UR - https://www.scopus.com/pages/publications/105018228776
U2 - 10.1109/ICPET66029.2025.11160437
DO - 10.1109/ICPET66029.2025.11160437
M3 - 会议稿件
AN - SCOPUS:105018228776
T3 - 2025 7th International Conference on Power and Energy Technology, ICPET 2025
SP - 759
EP - 764
BT - 2025 7th International Conference on Power and Energy Technology, ICPET 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Power and Energy Technology, ICPET 2025
Y2 - 4 July 2025 through 7 July 2025
ER -