Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network

Wenbin Liu; Wenzheng Shao; Yang Xin

doi:10.1117/12.2685821

15 August 2023 Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network

Wenbin Liu, Wenzheng Shao, Yang Xin

Author Affiliations +

Proceedings Volume 12719, Second International Conference on Electronic Information Technology (EIT 2023); 127190D (2023) https://doi.org/10.1117/12.2685821
Event: Second International Conference on Electronic Information Technology (EIT 2023), 2023, Wuhan, China

Abstract

Aiming at the current problems of low-voltage distribution network (LVDN) at present due to the untimely updating of the account in the early stage, which leads to the unclear relationship between customers and affects the operation, management and fault research and judgment of distribution network, this paper presents an automatic identification method of distribution network topology on the basis of clustering of historical voltage data and its fluctuation characteristics. Firstly, the three-phase voltage data and user terminal voltage of the adjacent substation in the research object station area are collected through the distribution intelligent terminal, and the multi-dimensional fluctuation characteristic parameters of the voltage at both ends are defined and calculated, and the global fluctuation characteristics and local fluctuation characteristics of the voltage series are mainly analyzed; Then, the dimension of the target data is then reduced using the t ⁃ sne algorithm; Finally, based on the characteristics of voltage fluctuation after dimensionality reduction, the correct relationship between substation transformers and users was obtained by using an improved K ⁃ means clustering algorithm for clustering substation transformers and users. The result of the example shows that the subordinate relationship between the user and the transformer in the topology of the target station area can be identified through the detailed analysis of the voltage measurement data at both ends of the target station area.

Citation Download Citation

Wenbin Liu, Wenzheng Shao, and Yang Xin "Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network", Proc. SPIE 12719, Second International Conference on Electronic Information Technology (EIT 2023), 127190D (15 August 2023); https://doi.org/10.1117/12.2685821

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Transformers

Reflection

Matrices

Data acquisition

Geographic information systems

Modeling

Research management

Keywords/Phrases

Search In:

Publication Years