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| Presentation | 2020-09-11 13:45 Proposal and Evaluation on Prediction Method for Electricity Using Probability of Missing Sensor Value Norifumi Hirata, Osamu Maeshima, Kiyohito Yoshihara (KDDI Research)  IN2020-27 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | VPP (Virtual Power Plant) is known as a system for electric power demand-supply adjustment. VPP is realized by controls of distributed electric power sources. VPP system uses a demand-supply adjustment market for demand-supply adjustment, and need to predict electric power demand and supply sources to bid the market. The success or failure of the demand-supply adjustment is evaluated by the difference between the transaction quantities in the market and the sum of the observation value of the electric power sensor. If a sensor of a power source has a missing value, an observation value of the power source is regarded as zero. A problem by missing observation value is increasing prediction error and wrong controls by the prediction error. VPP system need to a prediction method of observation value based on missing probability of electric sensors that is not an interpolation method of input data. Therefore, we propose a method to reduce the prediction error using missing probability. The missing probability is calculated separately for two types of missing. As a result of evaluating error of missing probability, we confirmed the error ratio by our proposed method is 1.56%, which was smaller than error ratio (2.14%) by the baseline method. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Time Series prediction / Missing Data / VPP / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 163, IN2020-27, pp. 31-36, Sept. 2020. | |
| Paper # | IN2020-27 | |
| Date of Issue | 2020-09-03 (IN) | |
| 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 | IN2020-27 |
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| Conference Information | |
| Committee | CS IN NS NV |
| Conference Date | 2020-09-10 - 2020-09-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Session management (SIP/IMS), Interoperability/Standardization, NGN/NwGN/Future networks, Cloud/Data center networks, SDN (OpenFlow, etc.)/NFV, IPv6, Machine learning, etc. |
| Paper Information | |
| Registration To | IN |
| Conference Code | 2020-09-CS-IN-NS-NV |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Proposal and Evaluation on Prediction Method for Electricity Using Probability of Missing Sensor Value |
| Sub Title (in English) | |
| Keyword(1) | Time Series prediction |
| Keyword(2) | Missing Data |
| Keyword(3) | VPP |
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| 1st Author's Name | Norifumi Hirata |
| 1st Author's Affiliation | KDDI Research, Inc. (KDDI Research) |
| 2nd Author's Name | Osamu Maeshima |
| 2nd Author's Affiliation | KDDI Research, Inc. (KDDI Research) |
| 3rd Author's Name | Kiyohito Yoshihara |
| 3rd Author's Affiliation | KDDI Research, Inc. (KDDI Research) |
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| Speaker | Author-1 |
| Date Time | 2020-09-11 13:45:00 |
| Presentation Time | 25 minutes |
| Registration for | IN |
| Paper # | IN2020-27 |
| Volume (vol) | vol.120 |
| Number (no) | no.163 |
| Page | pp.31-36 |
| #Pages | 6 |
| Date of Issue | 2020-09-03 (IN) |
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