JOURNAL ARTICLE

A Feature Extraction Method for Non-intrusive Load Identification

Wei WeiTao PengYe LiXianyu FengZisong JiangHeyang Yu

Year: 2022 Journal:   Journal of Physics Conference Series Vol: 2195 (1)Pages: 012008-012008   Publisher: IOP Publishing

Abstract

Abstract When some household appliances are running, the electrical quantities such as active power and reactive power will change slowly for a long time, which will affect the feature extraction of event-based non-intrusive load identification, resulting in low accuracy of load identification results. In view of this situation, a feature extraction method is proposed. Its core idea is that there is a certain law in the change of active power and reactive power in a very short time, and the curve can be fitted to speculate the values of these electrical quantities in the next time, so as to eliminate the influence. Based on this, a feature extraction method applied to non-intrusive load identification is realized. The test results show that this method can effectively improve the accuracy of non-intrusive load identification feature extraction data, and has good application value.

Keywords:
Identification (biology) Feature extraction Feature (linguistics) Power (physics) AC power Computer science Extraction (chemistry) Pattern recognition (psychology) Artificial intelligence

Metrics

3
Cited By
0.32
FWCI (Field Weighted Citation Impact)
4
Refs
0.51
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Smart Grid Energy Management
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Energy Load and Power Forecasting
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
© 2026 ScienceGate Book Chapters — All rights reserved.