| Item type |
学術雑誌論文 / Journal Article.(1) |
| 公開日 |
2018-03-01 |
| 書誌情報 |
en : IEEE Communications Magazine
巻 55,
号 10,
p. 46-51,
発行日 2017-10-13
|
| タイトル |
|
|
タイトル |
When Weather Matters: IoT-Based Electrical Load Forecasting for Smart Grid |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Smart grid |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Internet of things (IoT) |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
load forecasting |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
metering infrastructure |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
big data |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
李, 良知
太田, 香
董, 冕雄
|
| 室蘭工業大学研究者データベースへのリンク |
|
|
表示名 |
太田 香（OTA Kaoru） |
|
URL |
http://rdsoran.muroran-it.ac.jp/html/100000140_ja.html |
| 室蘭工業大学研究者データベースへのリンク |
|
|
表示名 |
董 冕雄（DONG Mianxiong） |
|
URL |
http://rdsoran.muroran-it.ac.jp/html/100000145_ja.html |
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Electrical load forecasting is still a challenging open problem due to the complex and variable influences, e.g. weather and time. Although, with the recent development of Internet of Things (IoT) and smart meter technology, people have obtained the ability to record relevant information on a large scale, traditional methods struggle in analyzing such complicated relationships for their limited abilities in handling non-linear data. In the paper, we introduce an IoT-based deep learning system to automatically extract features from the captured data, and ultimately, give an accurate estimation of future load value. One significant advantage of our method is the specially designed two-step forecasting scheme, which significantly improves the forecasting precision. Also, the proposed method is able to quantitatively analyze the influences of some major factors, which is of great guiding significance to select attribute combination and deploy on-board sensors for smart grids with vast area, variable climates and social conventions. Simulations demonstrate that our method outperforms some existing approaches, and can be well applied in various situations. |
|
言語 |
en |
| 出版者 |
|
|
出版者 |
IEEE |
|
言語 |
en |
| 出版者版へのリンク |
|
|
表示名 |
10.1109/MCOM.2017.1700168 |
|
URL |
https://doi.org/10.1109/MCOM.2017.1700168 |
| DOI |
|
|
関連タイプ |
isVersionOf |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
10.1109/MCOM.2017.1700168 |
| 日本十進分類法 |
|
|
主題Scheme |
NDC |
|
主題 |
007 |
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
0163-6804 |
| 権利 |
|
|
言語 |
en |
|
権利情報 |
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| 著者版フラグ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| フォーマット |
|
|
内容記述タイプ |
Other |
|
内容記述 |
application/pdf |
IEEECM_55_10_46_51 (1.5 MB)
