Noninvasive Load Identification Method Based on Feature Similarity
Joint Authors
Li, Hongyan
Ding, Xianfeng
Qu, Dan
Lin, Jiang
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-24
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
The traditional power load identification is greatly restricted in application because of its high cost and low efficiency.
In this paper, the similarity model is established to realize the noninvasive load identification of power by determining the feature database for the equipment.
Firstly, the wavelet decomposition method and the wavelet threshold processing method are used to remove abnormal points and reduce noise of the original data, respectively.
Secondly, the transient and steady-state characteristics of electrical equipment (active power and reactive power, harmonic current, and voltage-current trajectory) are extracted, and the feature database for the equipment is established.
Thirdly, the feature similarity is defined to describe the similarity degree of any two devices under a certain feature, and the similarity model of automatic recognition of a single device is established.
Finally, the device identification and calculation of power consumption are carried out for the part of data in annex 2 of question A in the 6th “teddy cup” data mining challenge competition.
American Psychological Association (APA)
Li, Hongyan& Ding, Xianfeng& Qu, Dan& Lin, Jiang. 2020. Noninvasive Load Identification Method Based on Feature Similarity. Journal of Electrical and Computer Engineering،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1183887
Modern Language Association (MLA)
Li, Hongyan…[et al.]. Noninvasive Load Identification Method Based on Feature Similarity. Journal of Electrical and Computer Engineering No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1183887
American Medical Association (AMA)
Li, Hongyan& Ding, Xianfeng& Qu, Dan& Lin, Jiang. Noninvasive Load Identification Method Based on Feature Similarity. Journal of Electrical and Computer Engineering. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1183887
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1183887