One-Key Sequential Control Technology for Intelligent Substation Based on Convolutional Neural Network and Natural Language Processing

Intelligent substations, as an important part of modern power grids, have been widely used in the automation control of power systems. Although the existing One-Key sequential control technology has significant results in improving operation efficiency and reducing the risk of misoperation, there are still major limitations in the efficiency of operation ticket writing and checking, as well as the manual error rate. In this paper, we propose a One-Key sequential control scheme for intelligent substations based on CNN and NLP technologies, aiming to improve the automation of generating and checking operation tickets by integrating these two technologies. This paper investigates the application of CNN in the recognition of main wiring diagrams of intelligent substations and explores the effectiveness of NLP in the verification of operation tickets and database signals. In order to verify the feasibility and practicality of the proposed scheme, this paper designs and implements a system architecture integrating CNN and NLP technologies, and conducts systematic tests on a 500 kV substation. The test results show that the technical scheme proposed in this paper can significantly improve the efficiency of generating and verifying operation tickets, reduce the errors caused by human intervention, and has wide application value and development potential.