Noninvasive Load Identification Method Based on Feature Similarity
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 w...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/3585606 |
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| _version_ | 1832566000837459968 |
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| author | Hongyan Li Xianfeng Ding Dan Qu Jiang Lin |
| author_facet | Hongyan Li Xianfeng Ding Dan Qu Jiang Lin |
| author_sort | Hongyan Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-731d65e7b5d94da1b92c5dee3570ba8f |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-731d65e7b5d94da1b92c5dee3570ba8f2025-02-03T01:05:25ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552020-01-01202010.1155/2020/35856063585606Noninvasive Load Identification Method Based on Feature SimilarityHongyan Li0Xianfeng Ding1Dan Qu2Jiang Lin3School of Science, Southwest Petroleum University, Sichuan, Chengdu 610500, ChinaSchool of Science, Southwest Petroleum University, Sichuan, Chengdu 610500, ChinaSchool of Mathematics and Statistics, Sichuan University of Science & Engineering, Sichuan, Zigong 643000, ChinaSchool of Science, Southwest Petroleum University, Sichuan, Chengdu 610500, ChinaThe 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.http://dx.doi.org/10.1155/2020/3585606 |
| spellingShingle | Hongyan Li Xianfeng Ding Dan Qu Jiang Lin Noninvasive Load Identification Method Based on Feature Similarity Journal of Electrical and Computer Engineering |
| title | Noninvasive Load Identification Method Based on Feature Similarity |
| title_full | Noninvasive Load Identification Method Based on Feature Similarity |
| title_fullStr | Noninvasive Load Identification Method Based on Feature Similarity |
| title_full_unstemmed | Noninvasive Load Identification Method Based on Feature Similarity |
| title_short | Noninvasive Load Identification Method Based on Feature Similarity |
| title_sort | noninvasive load identification method based on feature similarity |
| url | http://dx.doi.org/10.1155/2020/3585606 |
| work_keys_str_mv | AT hongyanli noninvasiveloadidentificationmethodbasedonfeaturesimilarity AT xianfengding noninvasiveloadidentificationmethodbasedonfeaturesimilarity AT danqu noninvasiveloadidentificationmethodbasedonfeaturesimilarity AT jianglin noninvasiveloadidentificationmethodbasedonfeaturesimilarity |