Active identification method of power network topology anomaly based on graph database

Hongjie Shen; Xianming Liu

doi:10.1117/12.3006191

10 October 2023 Active identification method of power network topology anomaly based on graph database

Hongjie Shen, Xianming Liu

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279949 (2023) https://doi.org/10.1117/12.3006191
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The conventional active identification method of power grid topology anomaly mainly uses the R bit continuity method to obtain the topology anomaly threshold, which is vulnerable to the influence of bus sequence approximation, resulting in a long time for topology inversion. Therefore, a new active identification method of power grid topology anomaly needs to be designed based on the graph database. That is, the graph database is used to generate the active identification and search process of power grid topology anomaly, establish the dynamic model of active identification of power grid topology, design the active identification algorithm of power grid topology anomaly, and thus realize the active identification of topology anomaly. The experimental results show that the designed active identification method for power grid topology anomaly based on graph database has a good recognition effect, and the inversion topology optimization time of different nodes is relatively short, which has high efficiency and certain application value, and has made certain contributions to reducing the risk of power grid operation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongjie Shen and Xianming Liu "Active identification method of power network topology anomaly based on graph database", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279949 (10 October 2023); https://doi.org/10.1117/12.3006191

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