Core Viewpoint - The article discusses the implementation opinions on promoting "Artificial Intelligence + Energy" for high-quality development, emphasizing the integration of AI technologies into various energy sectors to enhance efficiency, safety, and sustainability by 2027 and beyond [3][9][10]. Group 1: Overall Requirements - The initiative aims to deepen the integration of AI with the energy sector, focusing on enhancing innovation and application technology levels, and ensuring the safety and reliability of energy systems [10][11]. - By 2027, a preliminary integration system of energy and AI is expected to be established, with significant breakthroughs in core technologies and widespread applications [11][12]. Group 2: Accelerating Energy Application Scenarios - AI will be applied across various energy sectors, including power grids, new energy, and traditional energy sources, to optimize operations and enhance flexibility [4][17]. - Specific applications include virtual power plants, distributed energy storage, and intelligent microgrids, aimed at improving load control and dynamic response capabilities [4][19]. Group 3: Key Technology Supply - The focus is on addressing technical bottlenecks in the energy sector, such as data silos and high energy consumption in computing, by developing common key technologies [40]. - Emphasis is placed on building high-quality data sets, enhancing computational support, and improving model capabilities to meet the specific needs of the energy sector [40][41]. Group 4: Implementation Measures - The article outlines measures for effective implementation, including strengthening organizational frameworks, promoting collaborative innovation, and establishing standards for AI applications in the energy sector [42][43]. - Pilot demonstrations will be organized to showcase replicable and scalable AI applications in energy, encouraging cross-sector collaboration [44].