基于静态模型的光热储能电站发电量优化策略

目前国内的光热储能电站处于起步阶段，对提高其运行效率或提升发电量的研究多数是从储热介质或储热方式出发，从内部能量流入手的优化方式却鲜有研究。针对以上问题，文章提出了一种基于静态模型的光热储能电站发电量优化策略，以提高其发电量与电站运行效率。首先从光热储能电站的运行机理出发，对各子系统自身及之间的能量流进行合理简化，得到静态能量流数学模型；然后提出一种以光热储能电站发电量最大为目标函数，以上述静态能量流数学模型为约束条件的优化策略，针对控制过程中时滞环节产生的不利影响，利用Smith预估补偿予以克服；最后采用MATLAB对该优化策略进行仿真验证，结果表明该优化策略可以有效提高光热储能电站的发电量与运行效率。

Power Generation Optimization Strategy Based on Static Model for Concentrating Solar Power Plant

At present， the concentrating solar power （CSP） station is still in the initial stage and the research on the operating efficiency or generating capacity is majorly started from thermal storage medium or thermal storage. Little research has been done to optimize from the energy flow. In view of the above problem， a power generation optimization strategy based on the static model for CSP is established to improve power generation and operating efficiency. Firstly， according to the operating mechanism of the CSP station， the energy flows of subsystems and those among them are simplified reasonably， and the static energy flow mathematical model of CSP is obtained. Then， an optimization strategy， which takes the maximum amount of power generated by the CSP station as the objective function and the mathematical model of static energy flow as the restriction is proposed. The Smith Predictor is adopted to get over the negative effect caused by the time lag link. Finally， the MATLAB is used to verify the correctness of the optimization strategy. The results show that the optimization strategy can effectively improve the power generation and the operating efficiency of the CSP station.