基于工况划分的机组优化运行寻优方法

Optimization of Unit Operation based on Operating Condition

为了有效挖掘和利用电站机组运行过程中积累的海量数据,提出了一种基于工况划分的机组运行寻优方法。该方法基于多参数稳态指数有效工况判断方法选取机组稳定工况下的运行数据作为分析对象。以不可控边界条件机组负荷和环境温度为对象,利用模糊聚类方法实现机组工况划分,对可控参数进行维度归约选取各工况下对机组能耗影响较大的运行参数,对比相同工况下的历史数据和当前运行数据,输出较低能耗值对应的运行参数,实现机组运行优化和节能优化。以某300 MW机组为实例展开研究,结果表明该方法可为运行人员优化机组运行提供参考依据从而实现机组的高效经济运行。

To analysis and utilize the mass operation data stored in supervisory information system(SIS),a conception of optimization of units operation based on operating condition was proposed.This paper selected the historical data under stable operating condition by multi-parameter steady-state detection.According to the load of unit and ambient temperature,fuzzy clustering algorithms is applied to divide the operating conditions.Then the parameters which have great influence on energy consumption of the unit are selected by correlation analysis.With comparing the operating data and historical data which belong to the same operating condition,the proposed approach can achieve the target of optimization of the operation and energy-saving.The method was performed on a 300 MW unit,and the results show that the method proposed can provide reference for the operation of units.