我的订单 | 我的收藏 | 加入收藏 | 返回首页
暖通空调杂志社>期刊目次>2018年>第9期

基于聚类分析方法的地铁环控能耗分析

Energy consumption analysis of underground railway environmental control based on cluster analysis method

朱培根[1] 丁 茹[1] 陈 琦[2] 韦炜致[1]
[1]中国人民解放军陆军工程大学 [2]上海应用技术大学

摘要:

基于大数据理论,采用数据挖掘的聚类分析方法,对南京市地铁1号线各站环控能耗的逐时数据进行了聚类分析,利用SQL Server 2012软件对平均化后的车站环控逐日能耗数据进行分析处理,得到用能特性不同的5类车站。对第Ⅰ类车站空调季(5—10月)的逐时、逐日、逐月环控能耗进行了数据拟合与分析,建立了车站典型日逐时能耗的标准能耗模型,提出了用于能耗预测的峰值环控能耗系数概念,实现了各类车站的能耗预测。

关键词:环控能耗,地铁,数据挖掘,聚类分析方法,能耗分析,峰值环控能耗系数

Abstract:

Based on the theory of big data, carries out a cluster analysis on the environmental control energy consumption data of each station of underground railway Line 1 in Nanjing city using the cluster analysis method of data mining, analyses the average daily energy consumption data of the stations with SQL Server 2012 software, and obtains five types of stations based on different energy characteristics. Carries out the data fitting and analysis of the hourly, daily and monthly energy consumption in the air conditioning season (May to October) for I-type station. Establishes the standard energy consumption models for the typical day hourly energy consumption. Puts forward a concept of coefficient of peak environmental control energy consumption. Realizes the energy consumption forecast of all kinds of stations.

Keywords:environmentalcontrolenergyconsumption,undergroundrailway,datamining,clusteranalysismethod,energyconsumptionanalysis,coefficientofpeakenvironmentalcontrolenergyconsumption

    你还没注册?或者没有登录?这篇期刊要求至少是本站的注册会员才能阅读!

    如果你还没注册,请赶紧点此注册吧!

    如果你已经注册但还没登录,请赶紧点此登录吧!