Automated generation method of recommendation for effective energy utilization as a HEMS service

Takahiro Hosoe, Tadanori Matsui, Hiroaki Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Smart Grids and Home Energy Management System (HEMS) have been propagated by energy liberalization, and there is a demand for services, which are based on analysis of energy consumption data. For instance, a recommendation on effective utilization of home appliances in order to reduce power consumption. However, it is computationally expensive to analyze data in order to provide an energy-saving handbook, which recommends low-carbon life and is written in a natural language. This kind of service is called recommendation service. Existing automated recommendation services are constrained by the range of data usage, especially when using local information, such as status of surroundings, weather, residents' behavior, etc. The proposed method of automated generation of recommendation considers this background knowledge and information by using clustering methods. The result of a questionnaire which compared a handmade recommendation with the proposed fully-automated recommendation showed that 80% of the residents selected the automated recommendation because of its appropriateness.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages74-79
Number of pages6
ISBN (Electronic)9781509040759
DOIs
Publication statusPublished - 2016 Dec 8
Event7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 - Sydney, Australia
Duration: 2016 Nov 62016 Nov 9

Other

Other7th IEEE International Conference on Smart Grid Communications, SmartGridComm 2016
CountryAustralia
CitySydney
Period16/11/616/11/9

Keywords

  • Energy consumption
  • Machine learning
  • Smart grids

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Signal Processing

Fingerprint Dive into the research topics of 'Automated generation method of recommendation for effective energy utilization as a HEMS service'. Together they form a unique fingerprint.

  • Cite this

    Hosoe, T., Matsui, T., & Nishi, H. (2016). Automated generation method of recommendation for effective energy utilization as a HEMS service. In 2016 IEEE International Conference on Smart Grid Communications, SmartGridComm 2016 (pp. 74-79). [7778741] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartGridComm.2016.7778741