Title :
Electrical abnormality determination of the users based on EEMD
Author :
Xiaoqiang Zhong ; Zhiwei Guo ; Dongdong Xu ; Hao Zhong ; Yu Dong
Author_Institution :
FuJian Electr. Power Co., Fuzhou, China
Abstract :
Currently power supply enterprises have less attention on the behavior of users in electricity. It is difficult for them to find the abnormality of the power users in time. To solve this problem, this paper gave a method of abnormality determination based on EEMD. In the model, we decomposed electricity load signals into a number of intrinsic mode functions (IMF) and the residual trend. Different IMF components represent different disturbance factors of different cycles, and the residual trend represents the general trend rejecting the fluctuations. Based on the theory of power load clustering, we chose certain enterprise and got the electric load data. The correlation research of the data could be served as the diagnosis of electrical abnormality of users. The experiment shows that the method proposed in this paper can determine the electrical abnormality of users effectively.
Keywords :
consumer behaviour; electricity supply industry; fault diagnosis; fluctuations; pattern clustering; EEMD; IMF; disturbance factor; electric load data; electrical abnormality determination; electrical abnormality diagnosis; electricity load signal decomposition; ensemble empirical mode decomposition; fluctuation rejection; intrinsic mode function; power load clustering theory; power supply enterprise; users behavior; Correlation; Electricity; Empirical mode decomposition; Fluctuations; Market research; Power supplies; White noise;
Conference_Titel :
Intelligent Control and Information Processing (ICICIP), 2014 Fifth International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4799-3649-6
DOI :
10.1109/ICICIP.2014.7010314