Intelligent Error Prevention and Security Algorithm for Power Dispatch Based on Data Analysis

In today’s increasingly expanding and complex power grid, ensuring the safe and reliable operation of the power grid has become an important research direction facing the power industry. The traditional power dispatch method mainly relies on manual operation and experience for decision-making, which has the drawbacks of slow response speed, high risk of misoperation, and inability to be suitable for the operation of large power grids. In order to improve the automation and security of power dispatch operation, this article applies data analysis to intelligent error prevention and security algorithms, thereby improving the automation level and security of power dispatch. This article adopts advanced technologies such as data mining, pattern recognition, and machine learning to construct a comprehensive intelligent error prevention and security algorithm framework. The experimental results indicate that the application of data analysis can effectively identify potential risks in power grid operation and provide timely scheduling suggestions. The application of data analysis can enable algorithms to achieve faster response speed and accuracy, with a maximum scheduling accuracy of $\mathbf{9 7. 8 \%}$. It also has advantages in adaptability and distributed energy response.