智能能源管理系统:利用模糊逻辑进行充电控制

R. I. Areola, A.O. Adetunmbi, Thomas O. Okimi
{"title":"智能能源管理系统:利用模糊逻辑进行充电控制","authors":"R. I. Areola, A.O. Adetunmbi, Thomas O. Okimi","doi":"10.9734/jerr/2024/v26i41119","DOIUrl":null,"url":null,"abstract":"Aim: Charge controller that leverages fuzzy logic was developed to enhance the efficiency of traditional charge controllers. A model was constructed and assessed for its performance through MATLAB/Simulink. It allows for flexibility in controlling the variability of renewable energy sources. It also improves the efficiency and lifespan of energy storage systems while minimizing the impact on the grid and environment.  \nStudy of the design: The PV system consists of a PV module, PWM inverter, MPPT controller and DC-DC converter which are connected using MATLAB/Simulink environment. \nMethodology: we conducted validation tests to substantiate the advantages of our fuzzy charge controller. The creation of fuzzy rules was based on the system's performance and subsequently translated into precise values with the assistance of a fuzzy inference system. This Research Project was Completed in Two Months. \nResults: Our findings clearly demonstrate that the implementation of fuzzy logic control results in superior charge controller performance. This, in turn, safeguards against battery discharging and overcharging during unpredictable weather conditions. \nConclusion: These protective measures are made possible through the decision-making capabilities of the DC-DC buck-boost converter, which effectively regulates both the voltage and current output of the PV module.","PeriodicalId":508164,"journal":{"name":"Journal of Engineering Research and Reports","volume":"105 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligent Energy Management System: Harnessing Fuzzy Logic for Charge Control\",\"authors\":\"R. I. Areola, A.O. Adetunmbi, Thomas O. Okimi\",\"doi\":\"10.9734/jerr/2024/v26i41119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aim: Charge controller that leverages fuzzy logic was developed to enhance the efficiency of traditional charge controllers. A model was constructed and assessed for its performance through MATLAB/Simulink. It allows for flexibility in controlling the variability of renewable energy sources. It also improves the efficiency and lifespan of energy storage systems while minimizing the impact on the grid and environment.  \\nStudy of the design: The PV system consists of a PV module, PWM inverter, MPPT controller and DC-DC converter which are connected using MATLAB/Simulink environment. \\nMethodology: we conducted validation tests to substantiate the advantages of our fuzzy charge controller. The creation of fuzzy rules was based on the system's performance and subsequently translated into precise values with the assistance of a fuzzy inference system. This Research Project was Completed in Two Months. \\nResults: Our findings clearly demonstrate that the implementation of fuzzy logic control results in superior charge controller performance. This, in turn, safeguards against battery discharging and overcharging during unpredictable weather conditions. \\nConclusion: These protective measures are made possible through the decision-making capabilities of the DC-DC buck-boost converter, which effectively regulates both the voltage and current output of the PV module.\",\"PeriodicalId\":508164,\"journal\":{\"name\":\"Journal of Engineering Research and Reports\",\"volume\":\"105 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering Research and Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/jerr/2024/v26i41119\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Research and Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/jerr/2024/v26i41119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目的: 开发了利用模糊逻辑的充电控制器,以提高传统充电控制器的效率。通过 MATLAB/Simulink 构建了一个模型,并对其性能进行了评估。它可以灵活地控制可再生能源的变化。它还能提高储能系统的效率和寿命,同时最大限度地减少对电网和环境的影响。 设计研究:光伏系统由光伏模块、PWM 逆变器、MPPT 控制器和 DC-DC 转换器组成,并使用 MATLAB/Simulink 环境进行连接。方法:我们进行了验证测试,以证实我们的模糊充电控制器的优势。模糊规则的创建基于系统的性能,随后在模糊推理系统的帮助下转化为精确值。该研究项目在两个月内完成。成果:我们的研究结果清楚地表明,实施模糊逻辑控制后,充电控制器的性能更加出色。这反过来又防止了电池在不可预测的天气条件下放电和过度充电。结论直流-直流降压-升压转换器的决策能力有效地调节了光伏模块的电压和电流输出,从而使这些保护措施成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Intelligent Energy Management System: Harnessing Fuzzy Logic for Charge Control
Aim: Charge controller that leverages fuzzy logic was developed to enhance the efficiency of traditional charge controllers. A model was constructed and assessed for its performance through MATLAB/Simulink. It allows for flexibility in controlling the variability of renewable energy sources. It also improves the efficiency and lifespan of energy storage systems while minimizing the impact on the grid and environment.  Study of the design: The PV system consists of a PV module, PWM inverter, MPPT controller and DC-DC converter which are connected using MATLAB/Simulink environment. Methodology: we conducted validation tests to substantiate the advantages of our fuzzy charge controller. The creation of fuzzy rules was based on the system's performance and subsequently translated into precise values with the assistance of a fuzzy inference system. This Research Project was Completed in Two Months. Results: Our findings clearly demonstrate that the implementation of fuzzy logic control results in superior charge controller performance. This, in turn, safeguards against battery discharging and overcharging during unpredictable weather conditions. Conclusion: These protective measures are made possible through the decision-making capabilities of the DC-DC buck-boost converter, which effectively regulates both the voltage and current output of the PV module.
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
期刊最新文献
Resilience and Recovery Mechanisms for Software-Defined Networking (SDN) and Cloud Networks Experimental Multi-dimensional Study on Corrosion Resistance of Inorganic Phosphate Coatings on 17-4PH Stainless Steel Modelling and Optimization of a Brewery Plant from Starch Sources using Aspen Plus Innovations in Thermal Management Techniques for Enhanced Performance and Reliability in Engineering Applications Development Status and Outlook of Hydrogen Internal Combustion Engine
×
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