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SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION

Abstract: 

Non-intrusive load monitoring (a.k.a. power disaggregation) refers to identifying and extracting the consumption patterns of individual appliances from the mains which records the whole-house energy consumption. Recently, deep learning has been shown to be a promising method to solve this problem and many approaches based on it have been proposed. In this paper, we propose a sequence-to-subsequence learning method, which makes a trade-off between traditional sequence-to-sequence and sequence-to-point method, to balance the convergence difficulty in deep neural networks and the amount of computation in the inference period. We build our model based on conditional generative adversarial network that helps us avoid designing the loss function manually. In addition, we apply U-Net and Instance Normalization techniques to our model and demonstrate their effectiveness. Evaluations are performed on real-world data sets and we achieve the state-of-the-art performance.

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Paper Details

Authors:
Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia
Submitted On:
15 May 2020 - 5:10am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Yungang Pan
Paper Code:
MLSP-L4.6
Document Year:
2020
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Document Files

SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION.pdf

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[1] Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia, "SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5344. Accessed: Jul. 16, 2020.
@article{5344-20,
url = {http://sigport.org/5344},
author = {Yungang Pan; Ke Liu; Zhaoyan Shen; Xiaojun Cai; Zhiping Jia },
publisher = {IEEE SigPort},
title = {SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION},
year = {2020} }
TY - EJOUR
T1 - SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION
AU - Yungang Pan; Ke Liu; Zhaoyan Shen; Xiaojun Cai; Zhiping Jia
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5344
ER -
Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia. (2020). SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION. IEEE SigPort. http://sigport.org/5344
Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia, 2020. SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION. Available at: http://sigport.org/5344.
Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia. (2020). "SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION." Web.
1. Yungang Pan, Ke Liu, Zhaoyan Shen, Xiaojun Cai, Zhiping Jia. SEQUENCE-TO-SUBSEQUENCE LEARNING WITH CONDITIONAL GAN FOR POWER DISAGGREGATION [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5344