Using ANFIS to Predict Harmonic Distortion in Residential Building Loads: A case study in the Amazonian Region of Brazil

Albino Moisés Faro de Morais Junior, M. Tostes, U. Bezerra, T. M. Soares
{"title":"Using ANFIS to Predict Harmonic Distortion in Residential Building Loads: A case study in the Amazonian Region of Brazil","authors":"Albino Moisés Faro de Morais Junior, M. Tostes, U. Bezerra, T. M. Soares","doi":"10.24084/REPQJ16.291","DOIUrl":null,"url":null,"abstract":"With the increasing use of nonlinear loads in homes in Brazil comes the problem of harmonic injection in the power system and increasingly is a problem for the electric sector that needs to scale it. Knowing the loads that consume energy and inject harmonics into the system is important so that solutions are sought to make the use of the system more efficient and improve the quality of the energy that circulates in the electrical grid. This work presents simulations of DHTv and DHTi of a set of residences in order to predict the behaviour of the load over time, using previous measurements. The modelling is conducted using an ANFIS, which uses a neural network to adjust the parameters of the output that uses fuzzy rule to determine the output values of the system.","PeriodicalId":21007,"journal":{"name":"Renewable energy & power quality journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable energy & power quality journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24084/REPQJ16.291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

With the increasing use of nonlinear loads in homes in Brazil comes the problem of harmonic injection in the power system and increasingly is a problem for the electric sector that needs to scale it. Knowing the loads that consume energy and inject harmonics into the system is important so that solutions are sought to make the use of the system more efficient and improve the quality of the energy that circulates in the electrical grid. This work presents simulations of DHTv and DHTi of a set of residences in order to predict the behaviour of the load over time, using previous measurements. The modelling is conducted using an ANFIS, which uses a neural network to adjust the parameters of the output that uses fuzzy rule to determine the output values of the system.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
应用ANFIS预测住宅建筑荷载谐波畸变:以巴西亚马逊地区为例
随着巴西家庭使用非线性负载的增加,电力系统中的谐波注入问题也随之而来,这对需要扩大规模的电力部门来说日益成为一个问题。了解消耗能量和向系统注入谐波的负载是很重要的,这样才能寻求解决方案,使系统的使用更有效,并提高在电网中循环的能量的质量。这项工作提出了一组住宅的DHTv和DHTi的模拟,以便预测负载随时间的行为,使用以前的测量。采用ANFIS进行建模,利用神经网络调节输出参数,利用模糊规则确定系统输出值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A bibliometric study on the nexus of economic growth and renewable energy in Brazil Energy Flows Optimization in a Renewable Energy Community with Storage Systems Integration Effect of cloud transits in a stand-alone solar photovoltaic water pumping system MATLAB® Modeling of a Microgrid: Towards a Vision Based on Entropy Balance Self-Heating Induced Instability of a Non-Linear Inductor in a SMPS: a Case Study.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1