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基于FP-growth算法的电压事件干扰源定位方法

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定位电能质量干扰源是确定电力系统中电能质量污染责任并深化治理的前提.提出一种利用已有的海量电能质量监测数据,基于关联分析算法确定各监测节点在电压事件上的相互影响关系,进而定位干扰源的方法.在技术路线上,重点实现了对采自实际电网的电能质量监测数据的转换处理,使顺序存储的数据转为多节点按时间轴对齐的二维表,之后选用PF-growth算法,采用合适的参数,计算出各节点之间在电压事件上的影响关系.相对于传统的系统仿真和矩阵计算的方法,本文方法具有成本低、计算快速有效等特点.
A Method of Locating Voltage Disturbance Sources Based on FP-Growth Algorithm
Positioning disturbance sources is the prerequisite of defining the power quality pollution liability and improving the management of power system.This paper presents a method to analyze the mutual influence of the voltage events generated from the different nodes and then locate the voltage disturbance sources in a grid based on massive existing power quality monitoring data and association rule algorithm.Technically,a batch of actual power quality data from a single-node sequential list was transformed into a multi-node parallel two-dimensional table.Then the PFgrowth algorithm was adopted together with some appropriate parameters to calculate the affecting relationship on voltage events between the nodes.Compared with the traditional system simulation and matrix calculation methods,this method is superior in low cost,fast and efficient computing features.

power qualitydisturbance locationassociation rulesgrid data mining

许延祥、曹军威、许杏桃、陈兵、邓珂琳

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清华大学信息技术研究院,北京100084

江苏省电力公司电力科学研究院,南京211103

电能质量 干扰源定位 关联规则 电网数据挖掘

2014

华东电力
华东电力试验研究院有限公司

华东电力

CSTPCD
影响因子:0.551
ISSN:1001-9529
年,卷(期):2014.42(7)
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