发电行业大模型“擎源”亮相

Core Insights - The State Energy Group has officially launched the "Qingyuan" power generation model, a billion-level model aimed at creating an intelligent decision-making system covering safety, environmental protection, electricity trading, production regulation, and equipment maintenance [1][2] Group 1: Innovations and Features - The "Qingyuan" model achieves three major innovative breakthroughs: 1. It integrates multi-source heterogeneous data such as operational monitoring, equipment status, and meteorological conditions to create a full-stack product matrix of "model-intelligent agent-application," enabling efficient dynamic collaboration across business units [1] 2. It provides a comprehensive AI solution specifically designed for the power system, covering "source-network-load-storage" scenarios, achieving vertical integration of power production through intelligent technology [1] 3. It utilizes a fully domestic technology stack, combining reinforcement learning and multi-modal fusion technology to establish an adaptive training and decision-making framework, creating a closed-loop verification system covering the entire lifecycle of power generation [1] Group 2: Application and Impact - The "Qingyuan" model has been successfully applied in four major business areas: safety and environmental protection, electricity trading, production regulation, and equipment maintenance, covering 13 scenarios and deploying 41 intelligent agents, effectively addressing pain points such as high safety risks, difficult trading decisions, complex multi-energy coordination, and passive equipment operation and maintenance [1] - In the area of equipment maintenance, the model has been applied in 179 pilot power stations, where it has detected 2,633 defects over six months by monitoring real-time data and sensing minute changes, overcoming challenges related to early defect detection and quantification [2] - The State Energy Group plans to advance the "Qingyuan" model through three phases: pilot verification, large-scale promotion, and ecosystem co-construction, gradually opening API interfaces to industry chain partners to build an open ecosystem for the power generation industry [2]