Optimal Design of Intelligent Analysis and Control System for Power Grid Operation and Maintenance

With the high-speed growth of Grid scale and the promotion of power system reform, the operation pressure of State Grid of China increases, which puts forward higher requirements for the lean management and control ability of power grid operation. In this paper, an optimal intelligent analysis and c...

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Bibliographic Details
Published in2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC) pp. 1445 - 1449
Main Authors Gu, Zhaoliang, Zhu, Mengzhao, Zhu, Wenbing, Zhou, Jiabin, Zhu, Qingdong, Wang, Jian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2020
Subjects
Business
Control systems
data center
Data centers
Distributed databases
Inspection
intelligent analysis and control
Monitoring
operation inspection
Power Grid
Power grids
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Summary:With the high-speed growth of Grid scale and the promotion of power system reform, the operation pressure of State Grid of China increases, which puts forward higher requirements for the lean management and control ability of power grid operation. In this paper, an optimal intelligent analysis and control system for power grid operation and maintenance has been designed, which further integrates the information of regulatory cloud, big data analysis, robot inspection, and transmission channel visual monitoring systems. It can be used for the management and control of business scenarios and equipment status information in the whole process of operation and maintenance. The system can provide an overall overview of the main grid operation information of the power grid on the macro level, display the situation and information of single equipment on the micro level. As a result, the designed system can well support the development of intelligent operation and inspection business at provincial and municipal levels, and promote the transformation of transportation inspection mode from business process driven to equipment state driven.
DOI:10.1109/ITOEC49072.2020.9141678