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| Paper Abstract and Keywords | ||
| Presentation | 2013-07-09 14:55 An Optimization Method using Recurrent Neural Networks for Power Grid Systems with Various Topologies Keisuke Kimura, Takayuki Kimura, Kenya Jin'no (NIT)  NLP2013-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Because demands of electricity due to to rapid increasing of population growth, depletion of fossil fuels, and reducing greenhouse gas emissions, the renewable energy have widely been studied. Then, the renewable energy systems are implemented into many fields such as houses or buildings. Basically, supplying electric power by the renewable energies often becomes unstable. Then, implementation of sophisticated control strategy to maintain the supply systems stably is needed. From this view point, M. E. Gamez et al. proposed an optimal control method us- ing recurrent neural networks for the smart grid systems. In their method, the optimization problems for the smart grid system are regarded as the linear programming problems, and the problems are solved by the recurrent neural networks. Results indicate that the control method has much possibility to implement into the real-world systems. However, only small sizes of the smart grid systems are evaluated in the previous works. Then, we evaluated the control method by more realistic power grid systems in this report. From the results of computational experiments, the performance of the method is enhanced by the topologies of the power grid systems. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Recurrent Neural Network / Linear Programming Problem / Renewable Energy / Complex Network / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 113, no. 116, NLP2013-46, pp. 111-115, July 2013. | |
| Paper # | NLP2013-46 | |
| Date of Issue | 2013-07-01 (NLP) | |
| 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 | NLP2013-46 |
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| Conference Information | |
| Committee | NLP |
| Conference Date | 2013-07-08 - 2013-07-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Miyako Island Marine Terminal |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2013-07-NLP |
| Language | English (Japanese title is available) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Optimization Method using Recurrent Neural Networks for Power Grid Systems with Various Topologies |
| Sub Title (in English) | |
| Keyword(1) | Recurrent Neural Network |
| Keyword(2) | Linear Programming Problem |
| Keyword(3) | Renewable Energy |
| Keyword(4) | Complex Network |
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| 1st Author's Name | Keisuke Kimura |
| 1st Author's Affiliation | Nippon Institute of Technology (NIT) |
| 2nd Author's Name | Takayuki Kimura |
| 2nd Author's Affiliation | Nippon Institute of Technology (NIT) |
| 3rd Author's Name | Kenya Jin'no |
| 3rd Author's Affiliation | Nippon Institute of Technology (NIT) |
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| Speaker | Author-2 |
| Date Time | 2013-07-09 14:55:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2013-46 |
| Volume (vol) | vol.113 |
| Number (no) | no.116 |
| Page | pp.111-115 |
| #Pages | 5 |
| Date of Issue | 2013-07-01 (NLP) |
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