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Design of neuro-fuzzy based intelligent inference algorithm for energy-management system with legacy device

Authors
Choi, I.-H.Yoo, S.-H.Jung, J.-H.Lim, M.-T.Oh, J.-J.Song, M.-K.Ahn, C.-K.
Issue Date
2015
Publisher
Korean Institute of Electrical Engineers
Keywords
Adaptive network based fuzzy inference system (ANFIS); Home energy management system (HEMS); Legacy device; Training schedule notification
Citation
Transactions of the Korean Institute of Electrical Engineers, v.64, no.5, pp.779 - 785
Indexed
SCOPUS
KCI
Journal Title
Transactions of the Korean Institute of Electrical Engineers
Volume
64
Number
5
Start Page
779
End Page
785
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/95889
DOI
10.5370/KIEE.2015.64.5.779
ISSN
1975-8359
Abstract
Recently, home energy management system (HEMS) for power consumption reduction has been widely used and studied. The HEMS performs electric power consumption control for the indoor electric device connected to the HEMS. However, a traditional HEMS is used for passive control method using some particular power saving devices. Disadvantages with this traditional HEMS is that these power saving devices should be newly installed to build HEMS environment instead of existing home appliances. Therefore, an HEMS, which performs with existing home appliances, is needed to prevent additional expenses due to the purchase of state-of-the-art devices. In this paper, an intelligent inference algorithm for EMS at home for non-power saving electronic equipment, called legacy devices, is proposed. The algorithm is based on the adaptive network fuzzy inference system (ANFIS) and has a subsystem that notifies retraining schedule to the ANFIS to increase the inference performance. This paper discusses the overview and the architecture of the system, especially in terms of the retraining schedule. In addition, the comparison results show that the proposed algorithm is more accurate than the classic ANFIS-based EMS system. Copyright © The Korean Institute of Electrical Engineers.
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공과대학 (전기전자공학부)
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