中国电机工程学报2026，Vol.46Issue(7)：2615-2625,中插1,12.DOI:10.13334/j.0258-8013.pcsee.250056
考虑多级压缩机耦合特性的压缩空气储能系统功率跟踪控制
Power Tracking Control of Compressed Air Energy Storage System Considering Coupling Characteristics of Multi-stage Compressors
摘要
Abstract
The new-type power system imposes higher demands on the flexibility of compressed air energy storage regulation.However,traditional PID decoupling control struggles to achieve high-precision power command tracking for the energy storage side within safety operation constraints due to the complex coupling relationships between multi-stage compressors.To address this issue,this paper proposes a model predictive power tracking control strategy that takes into account the coupling characteristics between multi-stage compressors.Initially,a refined state-space dynamic model for the energy storage side,reflecting the coupling relationships between the state and control variables of each compressor,is constructed.Subsequently,the model is transformed into a simplified power prediction model,with the objective function being the minimization of power tracking error.A model predictive power tracking control strategy considering safety operation constraints is developed.Finally,a system dynamic simulation model is established using MATLAB/Simulink to investigate the open-loop characteristics and control variable coupling relationships.The proposed control strategy is compared with the PID decoupling control in terms of secondary frequency regulation performance under safe operation constraints.Results show that the control strategy proposed in this paper can significantly improve the power tracking accuracy.关键词
压缩空气储能/模型预测控制/多级压缩机耦合/动态模型/功率跟踪Key words
compressed air energy storage/model predictive control/multi-stage compressor coupling/dynamic model/power tracking分类
信息技术与安全科学引用本文复制引用
陈思源,陈来军,崔森,刘瀚琛,郭中杰,梅生伟..考虑多级压缩机耦合特性的压缩空气储能系统功率跟踪控制[J].中国电机工程学报,2026,46(7):2615-2625,中插1,12.基金项目
国家自然科学基金项目(青年项目)(52407115) （青年项目）
清华大学-丰田联合研究基金项目(20233930061) （20233930061）
中国博士后科学基金面上项目(2024M750349).Project Supported by National Natural Science Foundation of China(Young Scientistic Program)(52407115) （2024M750349）
Tsinghua University-Toyota Joint Research Fund Project(20233930061) （20233930061）
China Postdoctoral Science Foundation General Program(2024M750349). （2024M750349）
