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| Dynamic Modelling and Characterization of Large Capacity Advanced Adiabatic Compressed Air Energy Storage System |
| Hou Xinyu1,2, Miao Shihong1,2, Wang Tingtao1,2, Wang Jiaxu1,2, Wang Jie1,2, Yao Fuxing1,2 |
1. State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan 430074 China;
2. School of Electrical and Electric Engineering Huazhong University of Science and Technology Wuhan 430074 China |
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Abstract The intermittency and unpredictability of renewable energy sources, such as photovoltaic (PV) and wind power, pose significant challenges to grid stability. Advanced energy storage technologies have attracted considerable attention in both academic and industrial fields. Among them, advanced adiabatic compressed air energy storage (AA-CAES) is considered a promising solution for large-scale energy storage applications. Accurately characterizing the dynamic response and regulation capabilities of large-scale AA-CAES systems is essential. To this end, developing robust dynamic models and conducting systematic analyses are crucial.
To investigate the dynamic characteristics of the AA-CAES system, the interaction mechanisms of key physical parameters are analyzed. A dynamic modeling approach based on conservation laws and empirical formulas is employed to establish mathematical models for the multistage compressor and turbine. Additionally, dynamic models for other critical components, including the underground cavern, heat storage chamber, and heat exchanger, are systematically developed. Each component model is validated against experimental data from existing literature to ensure accuracy and reliability. By integrating the validated models of all critical components, a comprehensive dynamic model of the entire AA-CAES system is constructed. This model is then used to conduct full-condition dynamic simulations of the system's operational cycles, including “compression- shutdown-power generation” processes. The three dynamic characteristics of startup, shutdown, and ramp-up are also simulated for the system operating parameters.
The simulation analysis leads to the following conclusions. (1) The operating parameter variations of the key component models are consistent with actual conditions. The system's dynamic model accurately captures parameter variations under all operating conditions. (2) Through the dynamic analysis of the entire operation process, the evolution of multiple parameters in the ‘Compression-Stop-Generation’ process is determined. Specifically, during the generator startup process, the initial power ramp-up rate is relatively slow but eventually exceeds the rotor's ramp-up rate. The per-unit efficiency remains consistently higher than the per-unit speed. The inertia time constant is directly proportional to the startup time, whereas the rate of increase in turbine inlet air pressure is inversely proportional to the startup time. (3) Dynamic simulation of the AA-CAES system startup, climb, and shutdown processes. By establishing performance indices, the dynamic characteristics of the system are further clarified. During the startup process, a larger inertia time constant imposes greater limitations on the speed ramp-up rate. In contrast, a higher air pressure ramp-up rate results in a greater initial acceleration of speed. In the ramp-up phase, lower initial power generation results in larger fluctuations in rotor speed and output power, as well as longer ramp-up durations. During the shutdown process, turbine speed and power output are primarily determined by the pressure differential between the turbine inlet and outlet, with the shutdown time coinciding with the moment when the pressure differential reaches its minimum value.
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Received: 14 November 2024
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2025, Vol. 40 
