Health assessment method of regional power grid topology based on deep neural network

Li Cheng; Yuan Jiang; Duohong Xu; Li Cheng; Bei Zhang; Yanni Cui; Hongxia Hu; Jingzhong Liu

doi:10.1117/12.2637637

13 May 2022 Health assessment method of regional power grid topology based on deep neural network

Li Cheng, Yuan Jiang, Duohong Xu, Li Cheng, Bei Zhang, Yanni Cui, Hongxia Hu, Jingzhong Liu

Proceedings Volume 12248, Second International Conference on Sensors and Information Technology (ICSI 2022); 1224810 (2022) https://doi.org/10.1117/12.2637637
Event: 2nd International Conference on Sensors and Information Technology (ICSI 2022), 2022, Nanjing, China

Abstract

With the rapid development of social economy, users have higher requirements for power quality. As the last level of power system, the reliability research of distribution network has been paid more and more attention. However, due to the random failure of system components, some or even all of the system functions are lost, which brings more and more huge economic and social losses to the normal production and life of modern society. This paper analyzes the topology of distribution network by using deep neural network, reveals the influence of network topology similarity on reliability from the perspective of network graph theory, and obtains regular conclusions. On this basis, the failure rate level of key branches, grid structure and access location of distributed power generation are further evaluated. The mathematical relationship between network topology and reliability is described with the index as the medium. Finally, the linkage optimization of reliability index is realized through the optimization of the above indexes, which solves the unclear optimization objectives in traditional planning. It pursues local optimization and ignores global optimization. Experiments show that the research content of this paper can effectively evaluate the health of power grid structure, and provide a reference for the research of distribution network graph theory.

Citation Download Citation

Li Cheng, Yuan Jiang, Duohong Xu, Li Cheng, Bei Zhang, Yanni Cui, Hongxia Hu, and Jingzhong Liu "Health assessment method of regional power grid topology based on deep neural network", Proc. SPIE 12248, Second International Conference on Sensors and Information Technology (ICSI 2022), 1224810 (13 May 2022); https://doi.org/10.1117/12.2637637

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