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| Presentation | 2017-03-03 15:30 Demand Response Minimizing the Impact on the Consumers' Utility Towards Renewable Energy Ryo Kutsuzawa, Naoya Takemura, Akira Yamashita, Jun Matsumoto (Keio Univ.), Makoto Tanaka (GRIPS), Naoaki Yamanaka (Keio Univ.)  NS2016-226 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In the smart grid, each consumer has a smart meter that communicates with electricity companies and other consumers and gets to decide power consumption according to the electricity market price. Many renewable resources will be connected to the grid as part of a worldwide effort to reduce carbon emissions. Increasing renewable resources means increasing the number of "sellers". It is difficult to set a price of the energy market consist of multi-seller - multi-buyer. Also, Increasing sellers that use renewable energy resources introduces new challenges in scheduling and dispatching controllable resources to follow the net load and control the power balance in the system In this thesis, we define impact on consumers’ utility, i.e., the difference between consumers’ utility when they consume the optimal power and one when they reduce power consumption. Then we aim to minimize the impact. We propose two methods: One-Time Demand Response and Foresight Demand Response. Through simulation, we see proposed methods can improve consumers’ welfare. Foresight Demand Response also improve consumers’ welfare three times compared with One-Time Demand Response. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | smart grid / machine learning / demand response / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 484, NS2016-226, pp. 395-400, March 2017. | |
| Paper # | NS2016-226 | |
| Date of Issue | 2017-02-23 (NS) | |
| ISSN | Print edition: ISSN 0913-5685 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 | NS2016-226 |
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| Conference Information | |
| Committee | NS IN |
| Conference Date | 2017-03-02 - 2017-03-03 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | OKINAWA ZANPAMISAKI ROYAL HOTEL |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2017-03-NS-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Demand Response Minimizing the Impact on the Consumers' Utility Towards Renewable Energy |
| Sub Title (in English) | |
| Keyword(1) | smart grid |
| Keyword(2) | machine learning |
| Keyword(3) | demand response |
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| 1st Author's Name | Ryo Kutsuzawa |
| 1st Author's Affiliation | Keio University (Keio Univ.) |
| 2nd Author's Name | Naoya Takemura |
| 2nd Author's Affiliation | Keio University (Keio Univ.) |
| 3rd Author's Name | Akira Yamashita |
| 3rd Author's Affiliation | Keio University (Keio Univ.) |
| 4th Author's Name | Jun Matsumoto |
| 4th Author's Affiliation | Keio University (Keio Univ.) |
| 5th Author's Name | Makoto Tanaka |
| 5th Author's Affiliation | National Graduate Institute for Policy Studies (GRIPS) |
| 6th Author's Name | Naoaki Yamanaka |
| 6th Author's Affiliation | Keio University (Keio Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-03-03 15:30:00 |
| Presentation Time | 20 minutes |
| Registration for | NS |
| Paper # | NS2016-226 |
| Volume (vol) | vol.116 |
| Number (no) | no.484 |
| Page | pp.395-400 |
| #Pages | 6 |
| Date of Issue | 2017-02-23 (NS) |
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