基于信息物理融合的间接空冷机组冷端系统运行优化

CPS-based Operation Optimization Study of Indirect Air-cooling Unit Cold End System Under Summer Conditions

随着我国能源消费与供给革命不断推进,火电企业发展形势日益严峻,需要在新一代能源系统中提高自身竞争优势。在系统阐述电站信息物理融合系统(cyber physical system,CPS)的体系结构和应用模式的基础上,提出基于CPS的火电机组生产过程表征与运行优化方法,并针对间接空冷机组冷端系统优化开展模型验证与案例分析。采用数据驱动方法建立间接空冷机组冷端CPS模型;利用机组历史运行数据修正汽轮机级组效率曲线,构建汽轮机变工况模型;通过BP神经网络回归预测空冷塔出口水温,协同优化得到变频泵最佳运行频率。案例机组运行数据分析结果表明:采用该冷端CPS模型及优化策略可降低机组供电煤耗0.9g/kWh,有效提升机组经济性。

With the continuous development of revolution of energy consumption and supply in China, the development of thermal power plants are facing a severe situation that thermal power enterprises need to improve their competitiveness in new-generation power systems. The power generation mode based on cyber physical system(CPS) was proposed based on the general structure and application mode of the CPS for the working process modeling and operation optimization of cold-end system of indirect air-cooling power units. A data-driven mechanism analysis method was introduced to build the cold-end CPS model and guide operation. The history operation data of case unit was illustrated to modify the characteristic curves of stage efficiency for the off-design calculation of turbo-units. A back propagation neural network(BPNN) was built for forecasting the air cooling tower outlet water temperature. The optimal pump frequency was obtained by coupling simulation. The case study shows that the utilization of CPS-based modeling and optimizing strategy results in a 0.9 g/(kW·h) decrease in net coal consumption rate so as to improve the unit economic performance.