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Paper Abstract and Keywords
Presentation 2021-06-11 10:50
A Study on Prediction of Synchrophasor Time-Series Data of In-Campus Distribution Voltage Using Gaussian Process Regression
Munetaka Noguchi (Osaka Pref Univ.), Yoshihiko Susuki (Osaka Pref Univ./JST), Atsushi Ishigame (Osaka Pref Univ.) NLP2021-3 CCS2021-3
Abstract (in Japanese) (See Japanese page) 
(in English) Due to recent penetration of distributed energy resources, dynamics of power distribution systems have been complicated in terms of analysis and control, and thus the so-called micro Phasor Measurement Unit (PMU) with high-resolution capability has been researched.
In this report, we propose to use the so-called Gaussian Process Regression (GPR) for prediction of PMU time-series data on distribution voltage and demonstrate it using measurement data from the in-campus distribution network in Nakamozu Campus, Osaka Prefecture University, Japan.
Also, the GPR-based prediction is discussed in terms of learning of actions of the Koopman operator for nonlinear dynamical systems to Gaussian Processes (that is, Gaussian random variables).
Keyword (in Japanese) (See Japanese page) 
(in English) Distribution voltage / Synchrophasor / Time-series data / Prediction / Gaussian process regression / Koopman operator / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 61, NLP2021-3, pp. 10-13, June 2021.
Paper # NLP2021-3 
Date of Issue 2021-06-04 (NLP, CCS) 
ISSN Print edition: ISSN 0913-5685  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 NLP2021-3 CCS2021-3

Conference Information
Committee NLP CCS  
Conference Date 2021-06-11 - 2021-06-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NLP 
Conference Code 2021-06-NLP-CCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Prediction of Synchrophasor Time-Series Data of In-Campus Distribution Voltage Using Gaussian Process Regression 
Sub Title (in English)  
Keyword(1) Distribution voltage  
Keyword(2) Synchrophasor  
Keyword(3) Time-series data  
Keyword(4) Prediction  
Keyword(5) Gaussian process regression  
Keyword(6) Koopman operator  
1st Author's Name Munetaka Noguchi  
1st Author's Affiliation Osaka Pref Univ. (Osaka Pref Univ.)
2nd Author's Name Yoshihiko Susuki  
2nd Author's Affiliation Osaka Pref Univ./JST-PRESTO (Osaka Pref Univ./JST)
3rd Author's Name Atsushi Ishigame  
3rd Author's Affiliation Osaka Pref Univ. (Osaka Pref Univ.)
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Speaker Author-1 
Date Time 2021-06-11 10:50:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2021-3, CCS2021-3 
Volume (vol) vol.121 
Number (no) no.61(NLP), no.62(CCS) 
Page pp.10-13 
Date of Issue 2021-06-04 (NLP, CCS) 

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