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Paper Abstract and Keywords
Presentation 2019-05-24 11:15
Construction of a regression analysis model of the electricity market including weather data -- Economic analysis of price effect, energy conservation effect and social welfare effect --
Hiroyuki Ogura (Mitsubishi Electric Corp.), Shunsuke Managi (Kyushu Univ.), Masahiko Ishino (Bunkyo Univ.) KBSE2019-2 SWIM2019-2
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we constructed a regression analysis model of the electricity power market including weather data, using panel data of the power saving behavior in the home acquired by Nakanojo power demand response demonstration experiment in Gunma prefecture. At the same time, we used the Japan Wholesale Power Exchange (JEPX) data set (the total execution quantity, the market price). And we estimated the model coefficients and elasticity of the parameters (price, DR, temperature, sunlight hours) of the power demand change. As a result of our analysis, the DR effect of incentive type DR is larger than that of electric power type DR except in FY2017 winter season. In other words, because power is an essential product for the living environment and production activities of consumers, etc., we confirmed that benefit and economic rationality, such as comfort and productivity, was given priority over electricity prices, especially when power was tight, such as severe weather. By using the power market regression model including the weather data proposed in this paper, it is possible to predict the DR effect of electricity rate DR and incentive DR more accurately. And, it can be used for power supply balance adjustment.
Keyword (in Japanese) (See Japanese page) 
(in English) consumer electricity resources / social benefit effect / wholesale power market / demand response / price elasticity / panel data regression analysis / fixed effect / randam effect  
Reference Info. IEICE Tech. Rep., vol. 119, no. 57, SWIM2019-2, pp. 9-16, May 2019.
Paper # SWIM2019-2 
Date of Issue 2019-05-17 (KBSE, SWIM) 
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 KBSE2019-2 SWIM2019-2

Conference Information
Committee SWIM KBSE  
Conference Date 2019-05-24 - 2019-05-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Kikai-Shinko-Kaikan Bldg. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SWIM 
Conference Code 2019-05-SWIM-KBSE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Construction of a regression analysis model of the electricity market including weather data 
Sub Title (in English) Economic analysis of price effect, energy conservation effect and social welfare effect 
Keyword(1) consumer electricity resources  
Keyword(2) social benefit effect  
Keyword(3) wholesale power market  
Keyword(4) demand response  
Keyword(5) price elasticity  
Keyword(6) panel data regression analysis  
Keyword(7) fixed effect  
Keyword(8) randam effect  
1st Author's Name Hiroyuki Ogura  
1st Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric Corp.)
2nd Author's Name Shunsuke Managi  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Masahiko Ishino  
3rd Author's Affiliation Bunkyo University (Bunkyo Univ.)
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Speaker Author-1 
Date Time 2019-05-24 11:15:00 
Presentation Time 45 minutes 
Registration for SWIM 
Paper # KBSE2019-2, SWIM2019-2 
Volume (vol) vol.119 
Number (no) no.56(KBSE), no.57(SWIM) 
Page pp.9-16 
Date of Issue 2019-05-17 (KBSE, SWIM) 

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