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| 摘要: |
| 针对发电厂生产系统和信息管理系统的现状，研究了一套适合发电厂的数据仓库DW(Data Warehouse)设计方法，即全厂级数据模型指导下的自底向上开发策略．数据库／联机分析处理OLAP(On-Line Analytical Processing)服务器／客户端的三层体系结构，星型多维数据模型及以SCADA系统和MIS系统为主的数据源。在建立数据仓库的基础上．通过联机分析处理技术可对发电厂的发电量，蒸汽量等全厂生产、经营、管理的汇总数据进行多维分析，使最终用户可从多角度、多侧面观察数据仓库中的数据。数据挖掘方法可找出数据仓库数据中隐藏的有用信息和知识．可用于发电厂设备检修，负荷预测和上网报价等，辅助管理人员作出科学的决策。 |
| 关键词: 数据仓库 联机分析处理 数据挖掘 设备检修 |
| DOI： |
| 分类号:TM734 TP311.13 |
| 基金项目: |
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| Application of data warehouse technique in power plants |
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LIU Yu LI Ran
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| Abstract: |
| According to the actual conditions of power plant production system and MIS,a set of design methods are studied:the down-top development strategy under the guidance of the plant data model,the three-tier data warehousing architecture of database/OLAP(On-Line Analytical Processing) server / front-end tools,the star schema of multidimensional data model,and the suitable data source mainly composed by SCADA system and MIS. After the foundation of data warehouse,user can do multidimensional analysis of the integrated data of power plants,such as power generation,steam generation and so on,using OLAP technique. The data in data warehouse can thus be viewed in different ways. The useful information and knowledge hidden in warehouse data can be explored using data mining methods for equipment maintenance,load forecast,network bidding and scientific decision-making. |
| Key words: data warehouse,OLAP,data mining,equipment maintenance |
