First and second law analysis and operational mode optimization of the compression process for an advanced adiabatic compressed air energy storage based on the established comprehensive dynamic model

• Published in: Energy (Oxford) Vol. 263; p. 125882
• Main Authors: Chen, Wei, Bai, Jianshu, Wang, Guohua, Xie, Ningning, Ma, Linrui, Wang, Yazhou, Zhang, Tong, Xue, Xiaodai
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.01.2023
• Subjects: AA-CAES; Dynamic modeling; First and second law analysis; Operational mode optimization; AA-CAES; First and second law analysis; Operational mode optimization; Dynamic modeling
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2022.125882

Compressed air energy storage (CAES) possesses great application potential. The dynamic characteristic of the compression process is meaningful for the parameter optimization and control design of the CAES system. A dynamic model of the compression process for an advanced adiabatic CAES (AA-CAES) system is created on the basis of the principles of conservations of mass, momentum, and energy of an opening system. The reliabilities of the proposed model are verified from two aspects of the compressor model and air storage device model. Energy and exergy analysis indicates that the proposed model follows the first and second laws of thermodynamics. The exergy losses of each component are calculated for the whole dynamic process. Calculation results show that the exergy losses in the compressors are higher than those in the heat exchangers. A multi-objective optimization is conducted by Genetic Algorithm. The mass optimum solution can improve ηex and mair by 0.014% and 0.660%, respectively. Four operational modes are proposed and optimized to improve the compression efficiency. The thermal performances of the design condition and four operational modes are simulated and compared. The comparison results show that modes N2 and N1 are the better operational modes, with high efficiency and low power consumptions, respectively. •A complex dynamic model of compression process for CAES was established and tested.•The exergy losses in the compressors are higher than those in the heat exchangers.•Multi-optimization for parametric design was conducted by Genetic Algorithm method.•Modes of N1 and N2 are the better ones with high efficiencies and low consumptions.