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Paper Abstract and Keywords
Presentation 2021-05-28 15:15
Local-location and short-term solar power forecast system for marine environment observation devices
Tetsuo Imai (Hiroshima City Univ.), Satoshi Ichimaru, Kenichi Arai, Toru Kobayashi (Nagasaki Univ.) SC2021-8
Abstract (in Japanese) (See Japanese page) 
(in English) Marine environmental observatories for environmental assessment offshore are powered by renewable energy sources such as solar power. However, the amount of electricity generated by renewable energy sources is unstable, and weather forecasts are still not sufficiently accurate, resulting in frequent refueling of offshore instruments due to depletion of fuel cells. To reduce this problem, it is necessary to improve the accuracy of local and short-term forecasts of solar power generation. In this article, by commercial weather forecasts for multiple locations and multiple times, we propose an LSTM-based solar power forecasting method that can follow the "positional shift" and "time shift" of forecasts.
Keyword (in Japanese) (See Japanese page) 
(in English) LSTM / recurrent neural network / solar power generation / solar radiation forecast / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 51, SC2021-8, pp. 39-43, May 2021.
Paper # SC2021-8 
Date of Issue 2021-05-21 (SC) 
ISSN Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SC2021-8

Conference Information
Committee SC  
Conference Date 2021-05-28 - 2021-05-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Cyber-Physical-Social System、IOT, Machine Learning Application, etc general 
Paper Information
Registration To SC 
Conference Code 2021-05-SC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Local-location and short-term solar power forecast system for marine environment observation devices 
Sub Title (in English)  
Keyword(1) LSTM  
Keyword(2) recurrent neural network  
Keyword(3) solar power generation  
Keyword(4) solar radiation forecast  
1st Author's Name Tetsuo Imai  
1st Author's Affiliation Hiroshima City University (Hiroshima City Univ.)
2nd Author's Name Satoshi Ichimaru  
2nd Author's Affiliation Nagasaki University (Nagasaki Univ.)
3rd Author's Name Kenichi Arai  
3rd Author's Affiliation Nagasaki University (Nagasaki Univ.)
4th Author's Name Toru Kobayashi  
4th Author's Affiliation Nagasaki University (Nagasaki Univ.)
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Speaker Author-1 
Date Time 2021-05-28 15:15:00 
Presentation Time 25 minutes 
Registration for SC 
Paper # SC2021-8 
Volume (vol) vol.121 
Number (no) no.51 
Page pp.39-43 
Date of Issue 2021-05-21 (SC) 

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