| Presentation | 2021-11-18 A Proposal of the Control Method for Multiple Buildings with AI Techiques Koki Fujita, Shugo Fujimura, Yuwei Sun, Hiroshi Esaki, Hideya Ochiai, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, the use of AI techniques for controlling building facilities has begun to be proposed. In the future, buildings will be equipped with not only air conditioners but also solar panels, storage batteries, and a variety of other power equipment, and it is expected that machine learning can be used to control them efficiently. However, there have been few studies on how to control multiple targets simultaneously, or on complex situations in which electrical equipment in multiple buildings is controlled simultaneously. In this study, we set up a situation where there are multiple buildings and each building has air-conditioning equipment, solar panels, and storage batteries. As a machine learning method, we propose a method that uses reinforcement learning for each building and federated learning for the whole system by aggregating the information from multiple building models. In order to verify the performance of the proposed method, we conducted experiments to control the set temperature of air conditioners in each building on a simulator, and confirmed that the performance of the proposed method was improved by using federated learning in multiple buildings. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Building Control / Reinforcement learning / Federated learning / IoT |
| Paper # | CAS2021-38,MSS2021-18 |
| Date of Issue | 2021-11-11 (CAS, MSS) |
| Conference Information | |
| Committee | MSS / CAS / IPSJ-AL |
|---|---|
| Conference Date | 2021/11/18(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Atsuo Ozaki(Osaka Inst. of Tech.) / Hiroki Sato(Sony LSI Design) |
| Vice Chair | Shingo Yamaguchi(Yamaguchi Univ.) / Yoshinobu Maeda(Niigata Univ.) |
| Secretary | Shingo Yamaguchi(Hokkaido Univ.) / Yoshinobu Maeda(NEC) / (Sony LSI Design) |
| Assistant | Masato Shirai(Shimane Univ.) / Motoi Yamaguchi(TECHNOPRO) / Yohei Nakamura(Hitachi) / Takahide Sato(Univ. of Yamanashi) / Yasutoshi Aibara(Murata Manufacturing) |
| Paper Information | |
| Registration To | Technical Committee on Mathematical Systems Science and its Applications / Technical Committee on Circuits and Systems / Special Interest Group on Algorithms |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Proposal of the Control Method for Multiple Buildings with AI Techiques |
| Sub Title (in English) | |
| Keyword(1) | Building Control |
| Keyword(2) | Reinforcement learning |
| Keyword(3) | Federated learning |
| Keyword(4) | IoT |
| 1st Author's Name | Koki Fujita |
| 1st Author's Affiliation | The University of Tokyo(UTokyo) |
| 2nd Author's Name | Shugo Fujimura |
| 2nd Author's Affiliation | The University of Tokyo(UTokyo) |
| 3rd Author's Name | Yuwei Sun |
| 3rd Author's Affiliation | The University of Tokyo(UTokyo) |
| 4th Author's Name | Hiroshi Esaki |
| 4th Author's Affiliation | The University of Tokyo(UTokyo) |
| 5th Author's Name | Hideya Ochiai |
| 5th Author's Affiliation | The University of Tokyo(UTokyo) |
| Date | 2021-11-18 |
| Paper # | CAS2021-38,MSS2021-18 |
| Volume (vol) | vol.121 |
| Number (no) | CAS-249,MSS-250 |
| Page | pp.pp.7-12(CAS), pp.7-12(MSS), |
| #Pages | 6 |
| Date of Issue | 2021-11-11 (CAS, MSS) |