跨临界CO_(2)循环系统控制优化策略的研究进展

Research Progress of Control Optimization Strategies for Transcritical CO_(2) Cycle System

控制策略作为跨临界CO_(2)循环系统的重要组成部分,是保证系统高效节能运行的关键。介绍了系统最优排气压力经验计算和泊金汉π定理的反馈控制、基于梯度追踪和极值寻优的实时在线控制以及基于神经网络的预测控制等,详细分析了系统控制策略的发展历程和未来发展趋势,并总结如下:离线控制建立简单、成本低,但易受到环境因素和系统部件变化的影响而导致控制性能降低;实时在线控制策略可以实时追踪系统最大能源效率对应的排气压力,但由于寻优过程费时较长,导致控制系统的收敛时间过长;模型预测控制系统可以实现实时优化和快速收敛,有着良好的发展前景。结合新能源汽车、建筑供暖、轨道交通、商超冷藏、军工等实际场景对跨临界CO_(2)循环系统控制策略的应用特点和未来发展趋势进行分析,进一步说明了提高控制策略的适用性是未来研究的重要方向,并分析将广义预测控制、强化学习等具有自适应属性的方法应用于跨临界CO_(2)循环系统控制策略的可行性,同时探讨了开发适用于大规模循环系统和储能系统控制策略在我国“双碳”背景下的重要意义。

As an important part of the transcritical CO_(2) cycle system,the control strategy played the key role to ensure the high efficiency and energy saving operation of the system.Studies of control strategies were examined such as the feedback control based on the empirical calculation of the optimal diacharge pressure of the system and the Buckinghamπtheorem,the real-time online control based on gradient tracking and extreme seeking,and the predictive control based on the neural network,etc.The development history and future development trend of the system control strategy were analysed and summarized in detail.Off-line control was easy to establish with low cost,but it was easily affected by environmental factors and changes in system components,resulting in reducing control performance;The real-time online control strategy could track the discharge pressure corresponding to the maximum energy efficiency of the system in real time,but due to the long optimization process,the convergence time of the control system was too long.Model predictive control system could realize real-time optimization and rapid convergence,and had a good development prospect.Combined with the practical scenarios of new energy vehicles,building heating,rail transit,commercial refrigeration,military industry and other practical scenarios,the application characteristics and future development trend of the control strategy of the transcritical CO_(2) cycle system were explored,and it was further explained that improving the applicability of the control strategy was an important direction for future research.The feasibility of applying adaptive methods such as generalized predictive control and reinforcement learning to the control strategy of transcritical CO_(2) cycle system was proposed,and the significance of developing control strategy for large-scale cycle system and energy storage system in China with the background of“double-carbon”was discussed.