Intelligent Power Informatization: Advanced Data Processing and Security Enhancement Approaches

With the deepening energy transition and the advancement of smart grids, intelligent power informatization has become a crucial enabler for improving grid efficiency and reliability. This paper first reviews the definition, developmental background, and the current state of research—both domestic and international—in intelligent power informatization, and analyzes the challenges posed by surging data volumes, heterogeneous sources, and security protection. Building on this foundation, we propose a suite of advanced data-processing techniques, including integrated multi-source data acquisition and cleansing methods, as well as intelligent analysis and mining algorithms based on machine learning and deep learning, to achieve precise perception and prediction of power-system operational states. Simultaneously, to counter network attacks and data-leakage threats, we design a multi-layered network-security framework and a comprehensive data-security mechanism that combines encryption, access control, and privacy protection. A case study of a real-time smart-grid monitoring platform and corresponding experimental evaluation demonstrate the superiority of the proposed methods in both data-processing performance and security enhancement. Finally, we outline future research directions in large-scale deployment, cross-domain collaboration, and adaptive security.