基于复杂分段拟合的热电厂负荷优化分配

Optimal Load Distribution of the Thermal Power Plant Based on Complex Subsection Fitting

以某热电联产机组为例,通过大数据分析,利用考虑是否有中压抽汽以及是否投运高压加热器的复杂分段函数拟合方法替代性能试验等传统方法得到2台汽轮机进汽量及发电量计算值,此计算值与实际值相比平均绝对误差在3%以内,以此计算方法作为全厂负荷优化分配的理论依据;结合锅炉侧试验数据,建立负荷优化分配数学模型,采用穷举法,在保证计算精度、满足运行要求的前提下,分别对汽轮机和锅炉负荷寻求基于效率最优的负荷优化分配;随机采集一周历史数据进行该优化分配后,总标煤耗量平均降低0.415 t/h,总发电量平均增加0.101 MW/h,全年可降低生产成本约245.43万元。

Based on CHP units and big data analysis,complex subsection function fitting method,considering whether there is medium-pressure extraction and whether the high-pressure heater is put into operation,replaces traditional methods including performance test to conclude the air inflow of two steam turbines and the generation capacity,and the mean absolute error between the calculated value and the actual value is within 3%.The method provides a theoretical basis for optimal load distribution of power plants.Based on the boiler-side test data,a mathematical model of optimal load distribution is established,and the method of exhaustion is used to seek optimal load distribution of steam turbine and boiler loads with optimal efficiency;after random collection of the historical data in one week for the optimal load distribution,the total standard coal consumption is reduced by 0.415 t/h on average,and the total power generation increases by 0.101 MW/h on average,leading to an annual production cost reduction of about 2.4543 million yuan.