告别AI“黑盒子”！龙德缘电力张瑞：破解三大难题，推动用户侧电力智能化落地

Core Insights - The "AI + Energy Development Conference" held in Beijing focused on exploring new paths and opportunities for the integration of AI and the energy industry, attracting over 300 representatives from government, energy companies, and academia [1] Group 1: AI Applications in Energy - Longdeyuan Electric Group emphasizes AI applications in the user-side power distribution sector, differentiating from traditional generation and transmission applications [4] - The company has achieved breakthroughs in three main scenarios: intelligent operation and maintenance, electricity spot trading, and integrated scheduling of "source-network-load-storage" [4] - In intelligent operation and maintenance, AI technologies have significantly improved fault warning timeliness and accuracy, reducing operational costs [4] - In electricity spot trading, AI-driven quantitative trading models have increased returns by 3%-5% compared to traditional methods [4] - The integrated scheduling scenario utilizes AI for load forecasting, enhancing green electricity consumption and reducing customer electricity costs [4] Group 2: Challenges in AI Implementation - The company identifies three major challenges in AI practice: data issues, trust in AI strategies, and insufficient iteration of business models [5] - Data challenges include insufficient trading data and high costs of data collection due to non-standard communication protocols among different manufacturers [5] - Trust issues arise when AI strategies deviate from human judgment, particularly in critical areas like electricity trading, affecting profitability and production [5] - The current use of AI as a tool without fundamentally upgrading the business model limits the scalability of AI technology in the user-side power service [5] Group 3: Future Outlook - Longdeyuan Electric plans to continue focusing on the user-side power distribution sector, addressing data collection and AI model trust issues [5] - The company aims to optimize AI application solutions in the three identified scenarios and explore new business models empowered by AI [5] - The goal is to promote high-quality development of the integrated "source-network-load-storage" system, contributing to the construction of a new power system [5]