基于大数据的火电厂能耗评估模型的研究  

Research on Energy Consumption Evaluation Model of Thermal Power Plant Based on Large Data

作　　者：杨瀚钦 申晓留[1] 王默玉[1] 乔鑫[1] 刘瑞雪[1] 孙杨博 YANG Hanqin SHEN Xiaoliu WANG Moyu QIAO Xin LIU Ruixue SUN Yangbo(School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

机构地区：[1]华北电力大学控制与计算机工程学院,北京102206

出　　处：《电力科学与工程》2016年第12期1-4,共4页Electric Power Science and Engineering

基　　金：国家自然科学基金(71071053);北京市自然科学基金(9122021)

摘　　要：为了顺利开展节能降耗工作,火电厂需要准确评估自身能耗指标。现阶段能耗指标评估主要使用传统数理统计方法,这些方法难以挖掘数据深层次的信息。使用大数据分析方法中的多元线性回归方法,得出了一套煤耗指标评估模型,对某电厂600 MW发电机组实际运行数据进行了大数据分析,解决了传统能耗指标评估方法的缺陷。使用残差分析法对模型准确性进行了验证,得出了模型满足实际需要的结论。In order to carry out energy saving and consumption reduction, the thermal power plant needs to accurately assess its energy consumption index. The method of mathematical statistics is the most commonly used traditional evaluation of energy consumption indicators, but it cannot dig out the deep layers of information. Big data analysis method in the multivariate linear regression method is used in this paper to analyse the actual operation data of generating set. This paper puts forward a set of evaluation model of coal consumption, solves the defects of the traditional energy consumption index evaluation method. The model was evaluated by the method of residual error analysis, and the conclusion that the model can meet the requirements of the actual production was made.

关 键 词：大数据 多元线性回归 能耗评估 SPSS 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]