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| Presentation | 2017-02-18 15:00 Prediction Model for Electric Power Demand in Building on Field Data with Extended Goal Graph and Heterogeneous Mixture Modeling Noriyuki Kushiro, Ami Fukuda (KIT), Toshihiro Mega (MELTEC), Takuro Shimizu (KIT)  AI2016-31 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | For realizing energy management and demand response in buildings, standardized interfaces, e.g. BACnet and OpenADR, are introduced into building management systems. Huge amount of data, including conditions for spaces and equipment in buildings, are collected from each building and accumulated in an aggregation center via the interfaces. However, control methods for the energy management and the demand response are far behind penetration of these interfaces. As the reason for the delay, both methods for constructing prediction model on big field data and for controlling equipment based on the above prediction model, have not been established yet. We tried to establish the prediction model on two years’ field data. Extended goal graph extracting viewpoints for dividing data on analysis scenarios and explanatory variables, and heterogeneous mixture modeling establishing the perdition model with liner regression were introduced in the study. Results of the above trial are described in this paper. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Prediction Model for Electric Power Demand in Building / Extended Goal Graph / Heterogeneous Mixture Modeling / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 460, AI2016-31, pp. 39-44, Feb. 2017. | |
| Paper # | AI2016-31 | |
| Date of Issue | 2017-02-11 (AI) | |
| 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 | AI2016-31 |
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| Conference Information | |
| Committee | AI |
| Conference Date | 2017-02-18 - 2017-02-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | AI |
| Conference Code | 2017-02-AI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prediction Model for Electric Power Demand in Building on Field Data with Extended Goal Graph and Heterogeneous Mixture Modeling |
| Sub Title (in English) | |
| Keyword(1) | Prediction Model for Electric Power Demand in Building |
| Keyword(2) | Extended Goal Graph |
| Keyword(3) | Heterogeneous Mixture Modeling |
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| 1st Author's Name | Noriyuki Kushiro |
| 1st Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 2nd Author's Name | Ami Fukuda |
| 2nd Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 3rd Author's Name | Toshihiro Mega |
| 3rd Author's Affiliation | Mitsubishi Electric Building Techno-Service Corporation (MELTEC) |
| 4th Author's Name | Takuro Shimizu |
| 4th Author's Affiliation | Kyushu Institute of Technology (KIT) |
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| Speaker | Author-1 |
| Date Time | 2017-02-18 15:00:00 |
| Presentation Time | 30 minutes |
| Registration for | AI |
| Paper # | AI2016-31 |
| Volume (vol) | vol.116 |
| Number (no) | no.460 |
| Page | pp.39-44 |
| #Pages | 6 |
| Date of Issue | 2017-02-11 (AI) |
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