数据挖掘在电能质量监测数据分析中的应用
TM933; 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点,从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一.提出了一种基于数据挖掘技术的电能质量监测数据处理分析体系,包括数据清理、数据集成、聚类分析和相关性分析等技术.将所提体系应用于某城市电网电能质量监测网数据处理分析中,获得了有意义的电能质量指标变化规律,能为电网规划、调度和运行提供有价值的参考....
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| Published in | 电测与仪表 Vol. 54; no. 9; pp. 46 - 51 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
上海电力学院电气工程学院,上海,200090%国网上海电力公司电力科学研究院,上海,200437
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-1390 |
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| Abstract | TM933; 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点,从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一.提出了一种基于数据挖掘技术的电能质量监测数据处理分析体系,包括数据清理、数据集成、聚类分析和相关性分析等技术.将所提体系应用于某城市电网电能质量监测网数据处理分析中,获得了有意义的电能质量指标变化规律,能为电网规划、调度和运行提供有价值的参考. |
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| AbstractList | TM933; 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点,从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一.提出了一种基于数据挖掘技术的电能质量监测数据处理分析体系,包括数据清理、数据集成、聚类分析和相关性分析等技术.将所提体系应用于某城市电网电能质量监测网数据处理分析中,获得了有意义的电能质量指标变化规律,能为电网规划、调度和运行提供有价值的参考. 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点，从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一。提出了一种基于数据挖掘技术的电能质量监测数据处理分析体系，包括数据清理、数据集成、聚类分析和相关性分析等技术。将所提体系应用于某城市电网电能质量监测网数据处理分析中，获得了有意义的电能质量指标变化规律，能为电网规划、调度和运行提供有价值的参考。 |
| Abstract_FL | It is a main issue to find valuable information from the power quality (PQ) data because of its big volume,heterogeneity and low value density in the power quality monitoring system of the grid.An analysis system of the power quality monitoring based on the data mining technologies is presented in this paper,consisting of the technologies of the data cleaning,data fusion,cluster analysis,correlation analysis,and etc.The proposed analysis system is applied in the power quality data analysis of a certain city power quality monitoring system.The meaningful variation laws of the power quality indices are obtained,which can provide valuable reference to the grid planning,dispatch and operation. |
| Author | 林顺富 谢潮 汤波 潘爱强 周健 |
| AuthorAffiliation | 上海电力学院电气工程学院,上海200090 国网上海电力公司电力科学研究院,上海200437 |
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| Author_FL | Tang Bo Zhou Jian Pan Aiqiang Xie Chao Lin Shunfu |
| Author_FL_xml | – sequence: 1 fullname: Lin Shunfu – sequence: 2 fullname: Xie Chao – sequence: 3 fullname: Tang Bo – sequence: 4 fullname: Pan Aiqiang – sequence: 5 fullname: Zhou Jian |
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| DocumentTitleAlternate | The data mining application in the power quality monitoring data analysis |
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| Keywords | correlation analysis 电能质量 相关性分析 power quality data mining cluster analysis 聚类分析 数据挖掘 |
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| Notes | It is a main issue to find valuable information from the power quality （PQ） data because of its big volume, heterogeneity and low value density in the power quality monitoring system of the grid. An analysis system of the power quality monitoring based on the data mining technologies is presented in this paper, consisting of the technologies of the data cleaning, data fusion, cluster analysis, correlation analysis, and etc. The proposed analysis system is applied in the power quality data analysis of a certain city power quality monitoring system. The meaningful variation laws of the power quality indices are obtained, which can provide valuable reference to the grid planning, dispatch and operation. 23-1202/TH power quality, data mining, cluster analysis, correlation analysis Lin Shunfu1 , Xie Chao1 , Tang Bo1 , Pan Aiqiang2, Zhou Jian2 （1College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China 2. Electric Power Research Institute, SMEPC, Shanghai 200437, China） |
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| PublicationYear | 2017 |
| Publisher | 上海电力学院电气工程学院,上海,200090%国网上海电力公司电力科学研究院,上海,200437 |
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| Snippet | 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点，从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一。提出了一种基于数... TM933; 电能质量监测网产生的电能质量数据具有数据量大、数据异构严重以及价值密度低等特点,从数据中发现有价值信息是电能质量数据处理分析面临的主要问题之一.提出了一种... |
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| SubjectTerms | 数据挖掘 电能质量 相关性分析 聚类分析 |
| Title | 数据挖掘在电能质量监测数据分析中的应用 |
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