Application of Correlation Coefficient Method in Identifying Household-Transformer Relationship
DOI:
https://doi.org/10.54097/hset.v7i.1055Keywords:
Station area, Household-transformer relationship, Correlation analysis, Correlation coefficient, Station-user relationship identificationAbstract
Since the transformer will produce line loss in the process of distributing power to users, in order to obtain accurate and reliable line loss data, it is very important to identify the correctness of household transformer relationship. The correlation coefficient method can analyze the influence degree of indicators and indicators, indicators and research objects, it has certain advantages in measuring linear correlation and judging the correlation of random variables. Therefore, this paper takes the identification of the relationship between stations and households as the background, and uses the data of power supply, line loss rate and user power consumption as the support to calculate the three correlation coefficients of Pearson, Spearman and Kendall. Based on the calculation results, different stations and time periods are selected to test to verify the reliability of the correlation coefficient method. The test results show that the correlation analysis method combined with three correlation coefficient calculation methods can effectively distinguish whether the household change relationship exists. The technical method of correlation coefficient is more practical for solving the related problems of classification and identification.
Downloads
References
Guochang Li, Weiqiong Song, Huizhu Xian, Liu Han, Xiao Ye, Juan Yuan. Research and application of power meter station recognition method based on Zero crossing time and SNR Algorithm [J]. Electrical measurement and instrumentation, 2019, 56(07):148-152.
Ya Li, Rusen Fan,Wei Jiang, Junjie Yang, Tao Song, Qinxue Zhao. Research on Intelligent station area identification method based on BP neural network [J]. Electrical measurement and instrumentation, 2017, 54 (03): 25-30.
Alisha Ye, Jun Gu, Xiaoqiu Zhang. Intelligent station area identification technology based on spatial-temporal correlation of data [J]. Modern electronic technology, 2018, 41 (04): 30-33.
Xiaolin Song, Luhan Huang, Yunlong He, Yuanfeng Zhang, Lijian Chen, Yue Chen. A new method for identifying the relationship between satation area and households based on the data collected by smart meters * [J / OL]. Electrical measurement and instrumentation: 1-7.
Mingming Pan, Shiming Tian, Bo Wu, Jun Ye. Research on area identification and power stealing detection method based on smart meter data [J]. Smart power, 2017, 45 (12): 80-84.
W. Hu, Y. Liu, Q. Guo, J. Wang, Y. Wang and Z. Zhao, "Detection of users-transformer relationship in the secondary power distribution system with smart meter data," 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA), Kristiansand, Norway, 2020, pp. 449-454, doi: 10.1109/ICIEA48937.2020.9248159.
Xu Huang, Weiheng Wang, Shuang Wu, Wei Hu. Research on identification method of district-household relationship based on power consumption big data [J]. Power supply and consumption, 2019, 36 (10): 22-29.
L.Ping et al. "The Research of Users-transformer Relationship Verification Method Based on Data-driven," 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 2019, pp. 2550-2554, doi: 10.1109/ISGT-Asia. 2019.8881160.
Jiaju Wang, Zhongbing Wan, Zhongxiao He, Jia Wang, Zhi Xie, Xiao Wang. Identification method of station-household relationship based on multidimensional scale analysis and improved k-means [J]. Electrical automation, 2020, 42 (02): 56-59.
Zikuan Lian. Identification of topological relations of low voltage stations based on data driven [D]. Zhejiang University, 2020.
Zepu Gao, Yun Zhao, Yilan Yu, Yongjian Luo, Ziwei Xu, Lianmei Zhang. Low voltage distribution network topology identification method based on knowledge map [J]. Power system protection and control, 2020, 48 (02): 34-43.
Guochang Li. Topology identification method based on Lora technology and GPU acceleration [J]. Electrical measurement and instrumentation, 2019, 56 (21): 88-95.
Yong Xiao, Yun Zhao, Zhidong Tu, Bin Qian, Runmian Chang. Low voltage distribution network topology verification method based on improved Pearson correlation coefficient [J]. Power system protection and control, 2019, 47 (11): 37-43.
Yuanlin Li, Fan Deng, Jie Gong, Kang Fu. Identification and adjustment method of household variable relationship considering spatial constraints [J]. Computer knowledge and technology, 2018, 14 (28): 191-194 + 196.
H. Yu, S. Xia, W. Wei, B. Sun, C. Dong, X. He. "Improvement on Application of Gray Correlation Analysis in Intelligent Transformer Area Recognition," 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, 2018, pp. 1-4, doi: 10.1109/EI2.2018.8582387.
Chao Yuan. Research and development of low voltage distribution network area identification technology [D]. Dalian University of technology, 2014.
Di Fan, Shaoshan Li, Haitao Li, Wei Wang. Research on the application of key technology of user identifier in station area [J]. North China power technology, 2010 (07): 27-30.
Rui Yang. Research on user network identification technology in distribution area [D]. Xi'an University of technology, 2018.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
