基于信息物理融合的火电机组节能环保负荷优化分配

CPS-based Load Dispatching Model for the Energy Conversation and Emission Reduction of Thermal Power Units

能源互联网背景下,火电机组厂级负荷分配需要兼顾安全性、经济性、环保性和智能化,要求发电机组的物理系统、信息系统和控制系统深度融合、协调优化。信息物理融合系统(cyber-physical system,CPS)紧密融合了物理、通信和信息网络,为火电机组的智能优化负荷分配提供了新思路。文中在火电机组海量运行数据基础上,基于模糊粗糙集(fuzzy rough set,FRS)大数据处理方法,得到机组煤耗和污染物排放量物理模型与信息模型的对应关系;综合考虑经济和排放因素,建立基于物理信息融合(CP)的负荷分配模型。以某600 MW燃煤发电机组为案例进行模型模拟,结果表明,负荷指令由700 MW增至1 100 MW,煤耗率以及SO2、NOx和粉尘浓度降低范围分别为1.3 g/(kW·h)、3.4 mg/m3、2.5 mg/m3和1.6 mg/m3左右。

The emerging of energy internet calls for even higher requirements for the plant-level load dispatching of thermal power units in terms of safety,efficiency,cleanness and intelligence. The physical system,information system and control system of power units were supposed to deeply fused,coordinated and optimized. The cyber-physical system（CPS） integrates the physical,communication and information network,providing a new way for the intelligent load dispatching of thermal power units. With the large amount of operational data,FRS-based big data analytics was introduced to derive the correlation between the physical and information model of coal consumption and pollutant emission; considering the economic and pollutant emission factors,the CP-based load dispatching model was built. The model was simulated on the operation data of two 600 MW coal-fired power units,and the results show that the reduction range of coal consumption rate is 1.3 g/（k W？h）,and the concentration reduction range of SO2,NOx and dust is 3.4 mg/m3,2.5 mg/m3 and 1.6 mg/m3,respectively.