Home energy management based on Bayesian network considering resident convenience

Tomoaki Shoji; Wataru Hirohashi; Yu Fujimoto; Yasuhiro Hayashi

doi:10.1109/PMAPS.2014.6960597

Home energy management based on Bayesian network considering resident convenience

Tomoaki Shoji, Wataru Hirohashi, Yu Fujimoto, Yasuhiro Hayashi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479935611
DOIs	https://doi.org/10.1109/PMAPS.2014.6960597
Publication status	Published - 2014 Nov 17
Event	2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Durham, United Kingdom Duration: 2014 Jul 7 → 2014 Jul 10

Publication series

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

Conference

Conference	2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014
Country	United Kingdom
City	Durham
Period	14/7/7 → 14/7/10

Keywords

Bayesian network (BN)
demand response (DR)
home energy management system (HEMS)
machine learning
smart grid

ASJC Scopus subject areas

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

Access to Document

10.1109/PMAPS.2014.6960597

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Shoji, T., Hirohashi, W., Fujimoto, Y., & Hayashi, Y. (2014). Home energy management based on Bayesian network considering resident convenience. In 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings [6960597] (2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PMAPS.2014.6960597

Home energy management based on Bayesian network considering resident convenience. / Shoji, Tomoaki; Hirohashi, Wataru; Fujimoto, Yu ; Hayashi, Yasuhiro.

2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 6960597 (2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shoji, T, Hirohashi, W, Fujimoto, Y & Hayashi, Y 2014, Home energy management based on Bayesian network considering resident convenience. in 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings., 6960597, 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014, Durham, United Kingdom, 14/7/7. https://doi.org/10.1109/PMAPS.2014.6960597

Shoji T, Hirohashi W, Fujimoto Y , Hayashi Y. Home energy management based on Bayesian network considering resident convenience. In 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 6960597. (2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings). https://doi.org/10.1109/PMAPS.2014.6960597

Shoji, Tomoaki ; Hirohashi, Wataru ; Fujimoto, Yu ; Hayashi, Yasuhiro. / Home energy management based on Bayesian network considering resident convenience. 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. (2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Conference Proceedings).

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abstract = "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.",

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