一种基于数据挖掘的馈线可装容量模型分析方法
摘要：馈线作为配网运行最关键的设备之一,评估馈线供电能力是保障配网运行的重要手段。本文通过引入馈线组负荷同时系数和需要系数两个参数,构建计算模型,求解馈线可装容量以评估馈线供电能力。首先,通过聚类分析和神经网络预测等方法预测馈线组负荷同时系数。然后,将馈线各负荷根据其实际接入容量情况分为饱和负荷和未饱和负荷,采用灰色预测和神经网络相结合的组合预测方法计算未饱和负荷的需要系数。最后,将预测得到的两个系数代入馈线可装容量计算模型进行求解。实际算例分析表明:所提方法的计算结果具有一定的预测趋势,充分利用了馈线载流量,并兼顾了配电网运行的可靠性,对于指导电网营销部门业扩报装工作具有重要意义。
Abstract:Feeder is one of the most important equipment in distribution network, and it is an important mean to evaluate the power supply capability of distribution network. In this paper, the calculation method of the feeder available capacity is obtained by introducing two parameters, the load simultaneous factor and the demand factor, to evaluate the power supply capability. Firstly, the load simultaneous factor of feeder group is predicted by means of clustering analysis and neural network prediction. Then, according to the actual access capacity, loads in feeder group are divided into saturated and unsaturated loads, and the load needful coefficient can be obtained by combing prediction method of grey forecasting and artificial neural network prediction approach. Finally, the feeder available capacity can be calculated by putting the predicted two parameters into proposed model. The calculation results show that proposed method has certain prediction ability, which makes full use of the feeder load flow and considers the reliability of distribution network operation, and can provide meaningful data support for the power supply company.
标题：一种基于数据挖掘的馈线可装容量模型分析方法
英文标题：An Analysis Method of Feeder Available Capacity Based on Data Mining
作者：郑 勇, 孙 明, 曹照静, 董树锋, 夏圣峰, 陈辉河,
关键词：馈线可装容量, 负荷同时系数, 需要系数, 预测, 数据挖掘,
发表日期：2018-04-09
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