Development of prediction-based operation planning method for domestic air-conditioner with adaptive learning of installation environment

Ryoichi Kuroha, Yu Fujimoto, Wataru Hirohashi, Yoshiharu Amano, Shinichi Tanabe, Yasuhiro Hayashi

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

The world is more aware of the need for saving energy because of increasing world energy consumption and environmental problems. To promote saving energy in the domestic field, the use of home energy management systems (HEMSs) is rapidly spreading. The HEMS which has automatically controlling function can control domestic electrical appliances including air-conditioners (ACs). In this research, we focus on AC operation plans to improve thermal comfort and reduce electricity costs for residents. However, AC control planning is generally a difficult task because the operation results greatly depend on the environmental characteristics in which the HEMS is installed. To solve this problem, we proposed an AC planning method that accounts for environmental characteristics and uncertainty in prediction by using historical data.

元の言語English
ホスト出版物のタイトル2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538628904
DOI
出版物ステータスPublished - 2017 10 26
イベント2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 - Washington, United States
継続期間: 2017 4 232017 4 26

Other

Other2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
United States
Washington
期間17/4/2317/4/26

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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  • これを引用

    Kuroha, R., Fujimoto, Y., Hirohashi, W., Amano, Y., Tanabe, S., & Hayashi, Y. (2017). Development of prediction-based operation planning method for domestic air-conditioner with adaptive learning of installation environment. : 2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 [8085983] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT.2017.8085983