摘要
山地电力架空线路大多沿山架设,穿越树竹林,周边的树竹生长缺陷引发短路故障频繁发生,造成用电客户的大量投诉,用户体验满意度下降,抢修抢险费用大幅度攀升,严重影响供电公司的信誉和售电收益.为了提升用电客户的满意度和供电公司的售电受益,采用主成分分析方法提取了山地电力架空线路通道运维质量的3个主要影响因素,它们分别是树竹生长缺陷数、缺陷的消除数和通道运维资金使用合理度.对树竹的生长规律建立一个预测模型,从而得到树竹生长缺陷数的一个预测,根据预测结果划拨架空线路所在供电所的运维资金,消除树竹生长的缺陷数,再用Logistic回归模型,构建架空线路通道运维质量智能评估模型,使供电公司对架空线路运维实现基于数据决策的模式,尽可能保证供电线路零故障运行.
Most of the overhead power lines of mountain power systems are erected along the mountain ranges,crossing the tree and bamboo forests,and the surrounding tree and bamboo growth defects cause frequent short-circuit faults,resulting in a large number of complaints from customers,reduced user experience satisfaction and a significant increase in the cost of rush repair and rescue operations and seriously affecting power supply company's reputation and sales revenue.In order to improve the customer satisfaction and the power supply benefit of the power supply company,the paper uses the principal component analysis to extract three main influencing factors of the operation and maintenance quality of the mountain power overhead lines,namely,the number of defects in the growth of trees/bamboo,the number of defects eliminated and the reasonable use of the funds for channel operation and maintenance.A prediction model is established for the growth law of the tree/bamboo,and a prediction of the number of defects in their growth is obtained.The operation and maintenance funds of the power supply station where the overhead line is located are allotted according to the prediction results,Then the logistic regression model is used to construct an intelligent evaluation model for the operation and maintenance quality of the overhead line channel,so that the power supply company can realize the data decision-making mode for the overhead line operation and maintenance,and ensure the zero-fault operation of the power supply line as much as possible.
作者
易校石
刘念
YI Xiao-shi;LIU Nian(School of Mathematics and Statistics,Yili Normal University,Ili Kazak Autonomous Prefecture Xinjiang 835000,China;School of Mathematics and Statistics,Chongqing University,Chongqing 401331,China)
出处
《西南大学学报(自然科学版)》
CAS
CSCD
北大核心
2020年第1期124-133,共10页
Journal of Southwest University(Natural Science Edition)
基金
国家自然科学基金(11371384)
新疆维吾尔自治区青年博士人才培养项目(2017Q087)
关键词
架空线路
预测模型
数据决策
智能评估
overhead line
predictive model
data decision
intelligent assessment