基于模糊逻辑2型的sulselrabar系统短期负荷预测建模方法

M. Djalal
{"title":"基于模糊逻辑2型的sulselrabar系统短期负荷预测建模方法","authors":"M. Djalal","doi":"10.29099/ijair.v3i1.68","DOIUrl":null,"url":null,"abstract":"This research proposed a modeling approach for 24-hour short-term load forcasting based on fuzzy logic type-2. In this research we get an approach in designing load forecasting model, where previously still using conventional fuzzy logic. Implementation of load forecasting in this research is done on electrical system 150 kV Sulselrabar. Sulselrabar electrical system in its development has grown rapidly, therefore needed a study that to improve system performance, one of which is the study of short-term load forcasting. As the input data used load data from 2010 to 2016 on the same day that is January 8th. To see the accuracy of the results, two approaches are performed, ie fuzzy logic type-1 modeled using Simulink and fuzzy logic type-2 modeled using m-file Matlab. From the analysis results obtained, Mean Percentage Error (MAPE) is the smallest by using Fuzzy Logic Type-2 method, compared with Fuzzy Logic Type-1 method.. Where, MAPE for fuzzy logic type-1 method is 2.133371219%, and by using fuzzy logic type-2 method, MAPE is 1.729778866%.","PeriodicalId":334856,"journal":{"name":"International Journal of Artificial Intelligence Research","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A modeling approach for short-term load forcasting using fuzzy logic type-2 in sulselrabar system\",\"authors\":\"M. Djalal\",\"doi\":\"10.29099/ijair.v3i1.68\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research proposed a modeling approach for 24-hour short-term load forcasting based on fuzzy logic type-2. In this research we get an approach in designing load forecasting model, where previously still using conventional fuzzy logic. Implementation of load forecasting in this research is done on electrical system 150 kV Sulselrabar. Sulselrabar electrical system in its development has grown rapidly, therefore needed a study that to improve system performance, one of which is the study of short-term load forcasting. As the input data used load data from 2010 to 2016 on the same day that is January 8th. To see the accuracy of the results, two approaches are performed, ie fuzzy logic type-1 modeled using Simulink and fuzzy logic type-2 modeled using m-file Matlab. From the analysis results obtained, Mean Percentage Error (MAPE) is the smallest by using Fuzzy Logic Type-2 method, compared with Fuzzy Logic Type-1 method.. Where, MAPE for fuzzy logic type-1 method is 2.133371219%, and by using fuzzy logic type-2 method, MAPE is 1.729778866%.\",\"PeriodicalId\":334856,\"journal\":{\"name\":\"International Journal of Artificial Intelligence Research\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Artificial Intelligence Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29099/ijair.v3i1.68\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29099/ijair.v3i1.68","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

提出了一种基于模糊逻辑2型的24小时短期负荷预测建模方法。本文提出了一种基于模糊逻辑的负荷预测模型设计方法。本研究以Sulselrabar 150 kV电力系统为研究对象,进行负荷预测的实现。Sulselrabar电力系统在其发展中迅速成长,因此需要研究如何提高系统的性能,短期负荷预测的研究就是其中之一。由于输入数据使用的是2010年至2016年当天的负荷数据,即1月8日。为了检验结果的准确性,采用了两种方法,即使用Simulink建模的模糊逻辑类型1和使用m-file Matlab建模的模糊逻辑类型2。从分析结果来看,与模糊逻辑类型1方法相比,模糊逻辑类型2方法的平均百分比误差(MAPE)最小。式中,模糊逻辑类型1方法的MAPE为2.133371219%,模糊逻辑类型2方法的MAPE为1.729778866%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modeling approach for short-term load forcasting using fuzzy logic type-2 in sulselrabar system
This research proposed a modeling approach for 24-hour short-term load forcasting based on fuzzy logic type-2. In this research we get an approach in designing load forecasting model, where previously still using conventional fuzzy logic. Implementation of load forecasting in this research is done on electrical system 150 kV Sulselrabar. Sulselrabar electrical system in its development has grown rapidly, therefore needed a study that to improve system performance, one of which is the study of short-term load forcasting. As the input data used load data from 2010 to 2016 on the same day that is January 8th. To see the accuracy of the results, two approaches are performed, ie fuzzy logic type-1 modeled using Simulink and fuzzy logic type-2 modeled using m-file Matlab. From the analysis results obtained, Mean Percentage Error (MAPE) is the smallest by using Fuzzy Logic Type-2 method, compared with Fuzzy Logic Type-1 method.. Where, MAPE for fuzzy logic type-1 method is 2.133371219%, and by using fuzzy logic type-2 method, MAPE is 1.729778866%.
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:604180095
Book学术官方微信