Open AccessData-driven Tracing Method of Overload of Transmission Network Equipment
Author(s) -
Meng Li,
Wei Wu,
Yi Lin,
Tongyu Yan,
Pingfa Huang,
Shengyi Lin
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/546/5/052001
Subject(s) - tracing , resampling , computer science , data mining , fuzzy logic , power grid , transmission (telecommunications) , grid , power network , power (physics) , real time computing , reliability engineering , electric power system , algorithm , engineering , artificial intelligence , mathematics , telecommunications , physics , geometry , quantum mechanics , operating system
It is of great significance to the tracing of heavy load or overload (HOD) of power transmission network equipment for the precise investment and planning in power grid. The measurement system of power transmission network is increasingly accurate and intelligent, and a large amount of operation data was generated. Therefore, it is theoretically feasible for the tracing method based on big data is proposed for the HOD transmission network equipment. Firstly, the messy operation data generated by the power grid should be preprocessed, including data coding, cleaning and resampling. Secondly, estimation of the importance of independent variables of mutual information was solved out four characteristic quantities which have a great influence on HOD by game theory. Then, with the characteristic quantity as the label, the Fuzzy C-means (FCM) was used to cluster the HOD data into four categories, corresponding to four causes of HOD. Finally, an example is given to analyze the operation data of a city’s transmission network in 2019, which verifies the effectiveness and accuracy of the proposed method. Compared with the manual tracing method, the algorithm can greatly improve the efficiency.