Core Viewpoint - The article emphasizes the importance of integrating artificial intelligence (AI) into the energy sector to enhance innovation, ensure energy security, and support the transition to a green and low-carbon energy system [2][3][4]. Group 1: Strategic Guidance - The implementation of AI in the energy sector is seen as a strategic choice to seize opportunities in technological competition and industrial transformation [3][4]. - The release of the "Implementation Opinions" serves as a guiding framework for the energy industry to deeply integrate AI, providing direction and a blueprint for development [3][4]. Group 2: Clear Objectives - The "Implementation Opinions" outlines a systematic approach to the "AI + Energy" initiative, focusing on high-value application scenarios and enhancing innovative application technology levels [5]. - The initiative aims to drive a comprehensive transformation in the energy sector through coordinated planning and sustained efforts [5]. Group 3: Application Focus - The article highlights the need to overcome common bottlenecks in AI applications within the energy sector, such as insufficient high-value scenarios and low resource sharing [6]. - It identifies eight key high-value application areas, including AI + power grid and AI + renewable energy, to facilitate the integration of AI into the energy system [6]. Group 4: Practical Exploration - The Southern Power Grid Company has proactively engaged in AI practices, establishing significant infrastructure and launching the first self-controlled large model "Da Watt" [7]. - The company aims to support the construction of a new power system and energy system through its AI initiatives [7]. Group 5: Accelerating Application Scenarios - The development of AI in the energy sector is expected to address challenges posed by the transition to a new power system, enhancing the capacity for clean energy consumption [8][9]. - The company has planned over 350 application scenarios across various business domains, demonstrating significant empowerment effects [9]. Group 6: Strengthening Key Technology Supply - The article stresses the importance of core elements such as computing power, data, and models in supporting the development of AI in the energy sector [10]. - The establishment of a self-controlled computing power cluster and high-quality data sets is crucial for driving innovation in electric power AI [10]. Group 7: Ensuring Development Support - A comprehensive approach is needed to ensure the long-term and complex integration of AI and energy, including the establishment of AI companies and research centers [11]. - The company aims to build a high-level talent pool and foster collaborative development within the AI ecosystem [11]. Group 8: Embracing AI for Future Development - The Southern Power Grid is committed to leveraging its digital transformation achievements to create a "digital grid intelligent body" that promotes efficient human-machine collaboration [12]. - The company aims to contribute to national AI innovation and support global green and low-carbon energy transitions [12].

Core Viewpoint - The article emphasizes the urgent need for the integration of artificial intelligence (AI) in the energy sector, highlighting its role as a key technological engine for building a new energy system and driving industry innovation [3][4]. Group 1: Necessity for Breakthrough - AI is recognized as a strategic force leading a new wave of technological revolution and industrial transformation, significantly impacting energy production and consumption [3]. - Current AI applications in the energy sector are fragmented, leading to resource redundancy and systemic barriers, which hinder long-term development [3][4]. Group 2: Development Goals - The "Implementation Opinions" set two key development targets for 2027 and 2030, focusing on foundational work and establishing benchmarks in the initial phase, followed by comprehensive empowerment and ecosystem construction in the later phase [4]. - The 2027 goal aims to establish industry-level professional large models and typical scenario exploration, while the 2030 goal seeks to achieve world-leading levels in AI technology within the energy sector [4]. Group 3: Implementation Pathways - The article outlines a systematic approach to enhance the quality and efficiency of AI in the energy sector, focusing on key technological breakthroughs, widespread application of industry-level large models, and deep empowerment of high-value scenarios [5][6]. - Key technical directions include solidifying data foundations, enhancing computational power, and improving model capabilities to address common challenges in the energy sector [7]. Group 4: Deep Application of AI - The "Implementation Opinions" propose focusing on high-value application scenarios in areas such as power grids, new energy, and traditional energy sources, aiming to enhance AI's role in energy supply-demand balance and safety monitoring [9]. - The goal is to create an intelligent closed-loop system for perception, analysis, decision-making, and execution, driving energy security and green transformation [9]. Group 5: Innovation Ecosystem - The article stresses the importance of building an open and collaborative industrial ecosystem to support systemic changes in the energy sector [10]. - It highlights the need for pilot demonstrations to stimulate innovation, establish standard norms for orderly development, and strengthen collaborative innovation mechanisms [11][13][14].

聚变智能：以AI之力，奔赴能源终极梦想 近日，国家发展改革委、国家能源局联合印发《关于推进"人工智能+"能源高质量发展的实施意见》，明确提出推动人工智能技术在电 网、能源新业态、核电等多场景深度融合与应用。在"AI+能源"的政策引领下，一批企业正积极将技术创新转化为绿色实践，新奥集 团正是其中的典型代表。从遍布全国的低碳智能园区实践，到聚变人工智能的前瞻研发，新奥以"实战应用+前沿探索"双轮驱动，为能 源行业书写智能变革的生动注脚。 泛能实战：AI赋能，让能源"调得动"更"算得清" 政策的生命力在于落地，而新奥泛能网的核心价值，正是将人工智能从"技术概念" 转化为"可感知、可量化"的降碳效益与经济效益。 在虚拟电厂、园区综合能源管理、储能协同优化等核心场景中，新奥依托人工智能技术，交出了一份份能源智能转型的"绿色答卷"。 在浙江临平经开区，面对分布式光伏、用户侧储能、工业负荷等资源类型多、调度响应慢的难题，新奥搭建了虚拟电厂智慧运营平 台，以AI算法实现资源的规模化聚合与高效响应。该平台内嵌的需求响应策略可基于电网邀约自动生成优化响应计划，统筹企业、电 网及负荷聚合商三方目标，兼顾用户侧源网荷储平衡与可调节负 ...