Research on the Planning and Application Scenarios of Digital Brain for Power Enterprises Oriented to Digital Transformation

To address the urgent demand for real-time responsiveness and flexibility in scaling new energy integration and operating next-generation power systems, while resolving the longstanding challenges of "data silos" and "disconnect between management and technology" within power enterprises, this paper proposes and constructs a digital brain framework for power enterprises that deeply integrates management elements with data intelligence. Research indicates that constructing the digital brain must begin with the systematic digital transformation of management elements—including responsibilities, systems, and processes—to establish a unified, enterprise-level foundation of rules and data assets with clear accountability and standardized protocols. Building upon this foundation, this paper designs a technical architecture centered on a unified management platform and an enterprise data middle platform. Through the digital infusion of management rules and standardized services for data assets, it achieves closed-loop empowerment from data perception to intelligent decision-making. Avoiding broad scenario enumeration, this paper focuses on two core business domains: source-grid-load-storage coordinated dispatch and predictive equipment maintenance. It explains how the Digital Brain leverages multi-source data fusion, cloud-edge collaborative computing, and AI model chain technology to drive a fundamental shift in business models—from experience-driven to precision-intelligent decision-making. This research provides integrated guidance for power enterprises′ digital transformation—from top-level methodology to concrete implementation pathways—aiming to substantially enhance system operational efficiency, equipment reliability, and decision-making intelligence.