火电机组煤耗特征数据曲线在线自动拟合方法研究

Research on Online Automatic Fitting Method for Coal Consumption Characteristic Data Curve of Thermal Power Units

针对现有拟合方法对火电机组煤耗特征数据曲线进行拟合时存在拟合误差平方和过大,影响曲线拟合精度的问题,开展火电机组煤耗特征数据曲线在线自动拟合方法研究。首先,获取火电机组在运行中的时间、负荷、主蒸汽压力等参数,构建火电机组煤耗模型。其次,引入遗传算法,对煤耗特征数据曲线进行拟合。最后,实现拟合曲线在线自动生成。通过实例应用证明,新的拟合方法可有效降低拟合误差平方和,提高曲线拟合精度,提升煤耗特征数据利用价值,为火电机组数字化建设提供新方向。

In response to the problem of excessive square sum of fitting errors in current fitting methods for coal consumption characteristic data curves of thermal power units,which affects the accuracy of curve fitting,research has been conducted on online automatic fitting methods for coal consumption characteristic data curves of thermal power units.Firstly,obtain the parameters such as time,load,and main steam pressure of the thermal power unit during operation,and construct a coal consumption model for the thermal power unit.Secondly,genetic algorithm is introduced to fit the coal consumption characteristic data curve.Finally,achieve online automatic generation of fitting curves.Through practical applications,it has been proven that the new fitting method can effectively reduce the sum of squared fitting errors,improve curve fitting accuracy,enhance the utilization value of coal consumption characteristic data,and provide a new direction for the digital construction of thermal power units.