Lux and current analysis on lab-scale smart grid system using Mamdani fuzzy logic controller

B. Prasetyo, Faiz Syaikhoni Aziz, A. N. Handayani, Ari Priharta, A. I. C. Ani
{"title":"Lux and current analysis on lab-scale smart grid system using Mamdani fuzzy logic controller","authors":"B. Prasetyo, Faiz Syaikhoni Aziz, A. N. Handayani, Ari Priharta, A. I. C. Ani","doi":"10.14203/j.mev.2020.v11.11-21","DOIUrl":null,"url":null,"abstract":"The increasing need for electrical energy requires suppliers to innovate in developing electric distribution systems that are better in terms of quality and affordability. In its development, it is necessary to have a control that can combine the electricity network from renewable energy and the main network through voltage back-up or synchronization automatically. The purpose of this research is to create an innovative lux and current analysis on a lab-scale smart grid system using a fuzzy logic controller to control the main network, solar panel network and generator network to supply each other with lab-scale electrical energy. In the control, Mamdani fuzzy logic controller method is used as the basis for determining the smart grid system control problem solving by adjusting the current conditions on the main network and the light intensity conditions on the LDR sensor. Current conditions are classified in three conditions namely safe, warning, and trip. Meanwhile, the light intensity conditions are classified into three conditions namely dark, cloudy and bright. From the test results, the utility grid (PLN) is at active conditions when the load current is 0.4 A (safe) and light intensity is 1,167 Lux (dark). Then the PLN + PV condition is active when the load current is 1.37 (warning) and the light intensity is 8,680 lux (bright). Finally, the generator condition is active when the load current is 1.6 (trip) and the light intensity is 8,680 (bright). Based on the test results, it is known that the system can work to determine which source is more efficient based on the parameters obtained.","PeriodicalId":30530,"journal":{"name":"Journal of Mechatronics Electrical Power and Vehicular Technology","volume":"11 1","pages":"11-21"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mechatronics Electrical Power and Vehicular Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14203/j.mev.2020.v11.11-21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The increasing need for electrical energy requires suppliers to innovate in developing electric distribution systems that are better in terms of quality and affordability. In its development, it is necessary to have a control that can combine the electricity network from renewable energy and the main network through voltage back-up or synchronization automatically. The purpose of this research is to create an innovative lux and current analysis on a lab-scale smart grid system using a fuzzy logic controller to control the main network, solar panel network and generator network to supply each other with lab-scale electrical energy. In the control, Mamdani fuzzy logic controller method is used as the basis for determining the smart grid system control problem solving by adjusting the current conditions on the main network and the light intensity conditions on the LDR sensor. Current conditions are classified in three conditions namely safe, warning, and trip. Meanwhile, the light intensity conditions are classified into three conditions namely dark, cloudy and bright. From the test results, the utility grid (PLN) is at active conditions when the load current is 0.4 A (safe) and light intensity is 1,167 Lux (dark). Then the PLN + PV condition is active when the load current is 1.37 (warning) and the light intensity is 8,680 lux (bright). Finally, the generator condition is active when the load current is 1.6 (trip) and the light intensity is 8,680 (bright). Based on the test results, it is known that the system can work to determine which source is more efficient based on the parameters obtained.
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
基于Mamdani模糊逻辑控制器的实验室规模智能电网系统的Lux和电流分析
对电能日益增长的需求要求供应商在开发质量和可负担性更好的配电系统方面进行创新。在其发展过程中,有必要拥有一种能够通过电压备份或自动同步将可再生能源电网与主网相结合的控制。本研究的目的是在实验室规模的智能电网系统上创建一个创新的lux和电流分析,使用模糊逻辑控制器控制主网、太阳能电池板网络和发电机网络相互供应实验室规模的电能。在控制中,使用Mamdani模糊逻辑控制器方法作为基础,通过调整主网上的电流条件和LDR传感器上的光强条件来确定智能电网系统控制问题的解决方案。当前情况分为三种情况,即安全、警告和跳闸。同时,光照强度条件分为三种条件,即黑暗、多云和明亮。根据测试结果,当负载电流为0.4A(安全),光强度为1167Lux(黑暗)时,公用电网(PLN)处于活动状态。当负载电流为1.37(警告)并且光强度为8680勒克斯(明亮)时,PLN+PV条件激活。最后,当负载电流为1.6(跳闸)且光强度为8680(明亮)时,发电机状态为激活状态。根据测试结果,已知该系统可以根据所获得的参数来确定哪个源更有效。
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
CiteScore
0.70
自引率
0.00%
发文量
10
期刊最新文献
Five-axis parallel mechanism system (PMS) CNC partial link control system based on modified inverse kinematic of 6-DOF UPS parallel manipulator Impact of road load parameters on vehicle CO₂ emissions and fuel economy: A case study in Indonesia LSTM-based forecasting on electric vehicles battery swapping demand: Addressing infrastructure challenge in Indonesia Stability analysis of a hybrid DC-DC buck converter model using dissipation inequality and convex optimization Artificial intelligence in smart grids: A bibliometric analysis and scientific mapping 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学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
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