Home energy management based on Bayesian network considering resident convenience

Tomoaki Shoji, Wataru Hirohashi, Yu Fujimoto, Yasuhiro Hayashi

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Total electricity consumption in Japan increased rapidly and the power consumption per household is also continuing to increase. The framework of demand response (DR) to promote the reduction of electricity consumption in the household sector by regulating the price of the electricity will be introduced in the future. In this situation, residents must operate their appliances so as not to affect much to their lifestyles while taking into account the power cost. A home energy management system (HEMS) will have an essential role to control appliances such as air conditioners (ACs), battery energy storage systems (BESSs), electric vehicles (EVs), and heat pump water heaters (HPWHs) and automatically match their operations to the behavior of a resident when the electricity price changes. In this study, a Bayesian network, a fundamental tool of machine learning, is adapted to an HEMS to learn the behavior of the resident and appropriate operations of controllable appliances.

本文言語English
ホスト出版物のタイトル2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781479935611
DOI
出版ステータスPublished - 2014 11 17
イベント2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Durham, United Kingdom
継続期間: 2014 7 72014 7 10

出版物シリーズ

名前2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings

Conference

Conference2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014
CountryUnited Kingdom
CityDurham
Period14/7/714/7/10

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Control and Systems Engineering
  • Statistics and Probability

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