基于改进BP神经网络的10k V配电网线损评估方法

Li-ping Liu, Jianghong Bai, Yi-Tao Zhang, Mu Jiang, Yun-Chao Sun, Qi Wang
{"title":"基于改进BP神经网络的10k V配电网线损评估方法","authors":"Li-ping Liu, Jianghong Bai, Yi-Tao Zhang, Mu Jiang, Yun-Chao Sun, Qi Wang","doi":"10.1109/CICED.2018.8592255","DOIUrl":null,"url":null,"abstract":"A novel method of calculating 10kV distribution network line loss is proposed and realized by programming, which is improved BP neural network model based on adaptive genetic algorithm. Firstly, the characteristic index system is established according to electric characteristic parameters of samples. Then, through leaning the training samples by improved model of BPNN, the line loss evaluation model is obtained. After that,10kV line loss of test samples can be evaluated actually. The improved algorithm of BPNN is adopted to fit complex nonlinear relation between line loss and electric characteristic parameters. The 10kV distribution network in a real system is taken as an example. The accuracy of the proposed method is verified by simulation and calculation of the example. Compared with traditional BPNN, This method has the advantages of fast convergence and high accuracy.","PeriodicalId":142885,"journal":{"name":"2018 China International Conference on Electricity Distribution (CICED)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Evaluation Method of 10k V Distribution Network Line Loss Based on Improved BP Neural Network\",\"authors\":\"Li-ping Liu, Jianghong Bai, Yi-Tao Zhang, Mu Jiang, Yun-Chao Sun, Qi Wang\",\"doi\":\"10.1109/CICED.2018.8592255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel method of calculating 10kV distribution network line loss is proposed and realized by programming, which is improved BP neural network model based on adaptive genetic algorithm. Firstly, the characteristic index system is established according to electric characteristic parameters of samples. Then, through leaning the training samples by improved model of BPNN, the line loss evaluation model is obtained. After that,10kV line loss of test samples can be evaluated actually. The improved algorithm of BPNN is adopted to fit complex nonlinear relation between line loss and electric characteristic parameters. The 10kV distribution network in a real system is taken as an example. The accuracy of the proposed method is verified by simulation and calculation of the example. Compared with traditional BPNN, This method has the advantages of fast convergence and high accuracy.\",\"PeriodicalId\":142885,\"journal\":{\"name\":\"2018 China International Conference on Electricity Distribution (CICED)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 China International Conference on Electricity Distribution (CICED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICED.2018.8592255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 China International Conference on Electricity Distribution (CICED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICED.2018.8592255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

提出了一种基于自适应遗传算法的改进BP神经网络模型,并通过编程实现了10kV配电网线损计算的新方法。首先,根据样品的电特性参数建立特征指标体系;然后,利用改进的bp神经网络模型对训练样本进行学习,得到线损评估模型。在此基础上,可以对测试样品的10kV线路损耗进行实际评估。采用改进的bp神经网络算法拟合线损与电特性参数之间复杂的非线性关系。以实际系统中的10kV配电网为例。仿真和算例验证了所提方法的准确性。与传统的bp神经网络相比,该方法具有收敛速度快、精度高等优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Evaluation Method of 10k V Distribution Network Line Loss Based on Improved BP Neural Network
A novel method of calculating 10kV distribution network line loss is proposed and realized by programming, which is improved BP neural network model based on adaptive genetic algorithm. Firstly, the characteristic index system is established according to electric characteristic parameters of samples. Then, through leaning the training samples by improved model of BPNN, the line loss evaluation model is obtained. After that,10kV line loss of test samples can be evaluated actually. The improved algorithm of BPNN is adopted to fit complex nonlinear relation between line loss and electric characteristic parameters. The 10kV distribution network in a real system is taken as an example. The accuracy of the proposed method is verified by simulation and calculation of the example. Compared with traditional BPNN, This method has the advantages of fast convergence and high accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信