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基于孤立森林算法的台区线损分析与管理系统研究 被引量:1

Study on Station Line Loss Analysis and Management System Based on Isolated Forest Algorithm
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摘要 在"大数据"时代背景下,为解决台区线损管理低压客户庞杂及数据处理任务繁重的现象,设计基于孤立森林算法的台区线损分析与管理系统,介绍系统各子模块功能及设计方法,对孤立森林算法进行了分析,并采用孤立森林算法对用电数据进行深度挖掘。以某县用电数据为例,对系统实现加以说明,数据结果显示,孤立森林算法对用电数据异常检测有较高的准确性,该系统可有效提高低压配电台区线损管理效率。 Aiming at the current situation of large-scale low-voltage customers and heavy data processing tasks under the background of big data era,designing the line loss analysis and management system based on isolated forest algorithm.This paper introduces the functions and design methods of each sub-module of the system,analyzes the isolated forest algorithm,and uses the isolated forest algorithm to deeply mine the electricity data.Taking the electricity data of a certain county as an example,the implementation of the system is illustrated.The experimental results show that the isolated forest algorithm has a high accuracy in detecting abnormal electricity data,and the system can effectively improve the efficiency of line loss management in the low-voltage distribution platform area.
作者 周昕 张怡 王桢干 唐恬 ZHOU Xin;ZHANG Yi;WANG Zhen-gan;TANG Tian(State Grid jiangsu Electric Power co.LTD.,Yancheng Poiver Supply Company,Yancheng 224000,China)
出处 《电力学报》 2019年第6期578-584,共7页 Journal of Electric Power
关键词 用电系统信息数据 孤立森林 低压配电台区 线损分析 管理系统 power data information system isolated forest low voltage distribution station area line loss analysis management system
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  • 1曹一家,陈晓刚,孙可.基于复杂网络理论的大型电力系统脆弱线路辨识[J].电力自动化设备,2006,26(12):1-5. 被引量:218
  • 2IBM.风电场微观选址.IBM[EB/OL].(2014-08.17).http://www31.ibm.com/solutions/cn/industries/energy/thankyou/energy_wp.shtml.
  • 3中国电机工程学会信息化专委会.中国电力大数据发展白皮书(2013)[R].北京:中国电机工程学会,2013.
  • 4维克托.迈尔-舍恩伯格,肯尼斯.迈克耶.大数据时代:生活、工作与思维的大变革[M].杭州:浙江人民出版社,2013:1-23.
  • 5GeoModelSOLAR.用于能源系统的太阳能燃料[EB/OL].[2015-08].http://geomodelsolar.eu/cn.
  • 6Yu N P, Shah S, Johnson R, et al. Big data analytics in power distribution systems[C]//IEEE Power & Energy Society Innovation Smart Grid Technologies(ISGT)Conference. USA: Washington DC, 2015.
  • 7Rahman M N, Esmailpour A. An efficient electricity generation forecasting system using artificial neural network approach with big data[C]//IEEE First International Conference on Big Data Computing Service and Applications(Big Data Service). Redwood, CA: IEEE, 2015: 213-217.
  • 8CaprioloE,WamplerD,RutherglenJ.Hive编程指南(曹坤译)[M].北京:人民邮电出版社,2013:48-70.
  • 9John Russell. Getting started with Impala: interactive SQL for Apache Hadoop[M]. USA: Sebastopol, 2013: 36-40.
  • 10孟斌,张景秋,齐志营.北京市普通住宅空置量调查[J].城市问题,2009(4):6-11. 被引量:21

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