摘要
供电煤耗是衡量火电机组运行经济性的重要指标。本文提出一种基于并行随机森林算法的火电机组供电煤耗计算模型,利用某600 MW机组分布式控制系统(DCS)的海量数据,在Spark大数据平台,采用阈值判定出稳定工况的数据,采用局部异常因子算法对局部异常值进行检测与处理,采用K-means聚类算法确定出不同工况,最后筛选出影响机组供电煤耗的38个热力参数及其10种工况下211 615组数据。随机抽取其中4/5的数据对并行随机森林算法供电煤耗计算模型进行训练建模,1/5的数据进行测试,测试得到该模型供电煤耗计算值与实际值较吻合,平均绝对误差为1.79 g/(kW·h),相对误差在–3%~3%内。表明基于并行随机森林算法的供电煤耗计算模型计算精度较高,模型泛化能力较强,适用于供电煤耗计算。
Coal consumption for power supply is an important indicator to measure the economics of thermal power units.On the basis of parallel random forest algorithm,this paper proposes a calculation model of coal consumption for thermal power units.By using a large amount of DCS data of a 600 MW unit,on the platform of Spark big data,the data of stable working condition are determined by threshold,the local outliers are detected and processed by local anomaly factor algorithm,and the different working conditions are determined by K-means clustering algorithm.Finally,38 thermodynamic parameters affecting the coal consumption of power supply and 211 615 sets of data under 10 working conditions are screened out.4/5 of the data are randomly selected to train and model the coal consumption calculation model based on the parallel random forest algorithm,and the other 1/5 data is tested.The results show that,the calculated value of the model is in good agreement with the actual value.The average absolute error is 1.79 g/(kW·h),and the relative error is within–3%~3%,indicating this coal consumption calculation model based on parallel stochastic forest algorithm has high accuracy and strong generalization ability,which is suitable for power supply coal consumption calculation.
作者
文雯
刘文哲
肖祥武
向春波
谢小鹏
姜鑫
WEN Wen;LIU Wenzhe;XIAO Xiangwu;XIANG Chunbo;XIE Xiaopeng;JIANG Xin(Hunan Datang Xianyi Technology Co.,Ltd.,Changsha 410007,China)
出处
《热力发电》
CAS
北大核心
2018年第9期9-14,共6页
Thermal Power Generation
基金
中国大唐集团公司总部科技项目两化融合新技术在火电机组中的应用研究(201709)~~
关键词
火电机组
供电煤耗
随机森林
大数据
K-MEANS聚类
预测模型
thermal power unit
power supply coal consumption
random forest
big date
K-means clustering
predictive model
作者简介
第一作者简介:文雯(1989—),女,硕士研究生,主要研究方向为大数据技术在火电厂的应用,hncswenwen@163.com。
