Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Xie, Zhenpinga; b; * | Jiang, Siweib | Zhou, Jianianc
Affiliations: [a] School of Digital Media, Jiangnan University, Wuxi, Jiangsu, PRC, China | [b] Jiangsu Key Laboratory of Media Design and Software Technology (Jiangnan University), Wuxi, Jiangsu, PRC, China | [c] Guangzhou Intelligent Power Technology Co. Ltd., Guangzhou, Guangdong, RPC, China
Correspondence: [*] Corresponding author. Zhenping Xie, E-mail: xiezhenping@hotmail.com.
Abstract: For non-intrusive power load monitoring problem, the key trouble is that there contains complex multiple types of appliances in a power load environment. In this study, two key suppositions are firstly introduced: (1) the signal characteristics should keep stable for each load appliance with a same running state in continuous times; (2) there is at most one running state change at an enough small monitoring period. Then, we consider that a probabilistic label value for each possible load can be evaluated according to a probabilistic clustering principle. Moreover, a coupled allocation mechanism on mixed probabilistic labels is introduced, in which an iterative filtering strategy is designed to estimate the optimal state combination of different loads. By performing professional load scenario simulations, the algorithm performance is effectively examined. The corresponding results indicate that better comprehensive performance can be obtained by the proposed method compared to the latest hidden Markov model and fuzzy clustering method.
Keywords: Noninvasive power load monitoring, coupled allocation, probabilistic clustering, hidden Markov model, fuzzy clustering
DOI: 10.3233/JIFS-181319
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5435-5442, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl