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| Presentation | 2021-11-27 14:10 Studies of maximum electricity forecasting model including electricity market price -- Time series analysis with extra regressors added -- Hiroyuki Ogura (Nihon Univ.), Shunsuke Managi (Kyushu Univ.)  SWIM2021-27 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | As one of the solutions to the difficult problem of achieving both stable electricity supply and decarbonization, improving the forecasting accuracy of daily maximum electricity demand is a necessary condition. By improving the forecasting accuracy, it is possible to adjust the supply and demand when electricity is tight. In this paper, we constructed a daily maximum electricity demand forecasting model using electricity supply and demand data, meteorological data, and wholesale electricity market transaction price data in the TEPCO area since April 2016. First, we constructed a multiple regression forecasting model and statistically analyzed the correlation coefficient and regression coefficient for each explanatory variable (regression factor) including the wholesale electricity market price. Next, we added "date" to the explanatory variables and constructed a time-series forecasting model that considered the time-series data as the multiplication of the periodic functions of "weekly" and "annual" and the long-term change "trend". As a result, we improved the accuracy of forecasting the daily maximum electricity demand. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | electricity deregulation / electricity trading market / decarbonization society / demand forecasting / regression analysis / time series analysis / machine learning / explainability | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 274, SWIM2021-27, pp. 7-14, Nov. 2021. | |
| Paper # | SWIM2021-27 | |
| Date of Issue | 2021-11-20 (SWIM) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
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 | SWIM2021-27 |
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| Conference Information | |
| Committee | SWIM |
| Conference Date | 2021-11-27 - 2021-11-27 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SWIM |
| Conference Code | 2021-11-SWIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Studies of maximum electricity forecasting model including electricity market price |
| Sub Title (in English) | Time series analysis with extra regressors added |
| Keyword(1) | electricity deregulation |
| Keyword(2) | electricity trading market |
| Keyword(3) | decarbonization society |
| Keyword(4) | demand forecasting |
| Keyword(5) | regression analysis |
| Keyword(6) | time series analysis |
| Keyword(7) | machine learning |
| Keyword(8) | explainability |
| 1st Author's Name | Hiroyuki Ogura |
| 1st Author's Affiliation | Nihon University (Nihon Univ.) |
| 2nd Author's Name | Shunsuke Managi |
| 2nd Author's Affiliation | Kyushu University (Kyushu Univ.) |
| 3rd Author's Name | |
| 3rd Author's Affiliation | () |
| 4th Author's Name | |
| 4th Author's Affiliation | () |
| 5th Author's Name | |
| 5th Author's Affiliation | () |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2021-11-27 14:10:00 |
| Presentation Time | 45 minutes |
| Registration for | SWIM |
| Paper # | SWIM2021-27 |
| Volume (vol) | vol.121 |
| Number (no) | no.274 |
| Page | pp.7-14 |
| #Pages | 8 |
| Date of Issue | 2021-11-20 (SWIM) |
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