Experimental and analysis on household electronic power consumption

被引:4
|
作者
Qin, Jing [1 ]
机构
[1] Northeastern Univ, Wenhua Rd, Shenyang 110819, Peoples R China
关键词
Power consumption; Household electric; Linear model; Neural network model;
D O I
10.1016/j.egyr.2022.02.270
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Household power consumption helps the power supply department understand the power consumption of residents and whether there will be some abnormal power consumption phenomena. Taking the individual household electric power consumption dataset as an example, this paper establishes an extensible experimental analysis framework and analyzes the data in a visual way. In the experiment, the effects of linear regression model and neural network model on different characteristics are compared. The experiment shows that the effect of neural network model is better than linear regression model in the experimental dataset. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 2021 The 2nd International Conference on Power Engineering, ICPE, 2021.
引用
收藏
页码:705 / 709
页数:5
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