Core Insights - The article highlights the integration of artificial intelligence (AI) in the energy sector, emphasizing its potential to enhance efficiency and address challenges such as the intermittency of renewable energy sources [1][4][12] AI and Energy Development - The National Development and Reform Commission and the National Energy Administration of China have issued guidelines to promote the integration of AI and energy for high-quality development [1] - The energy industry is experiencing a "smart transformation," with AI technologies being applied to improve production efficiency and optimize energy management [6][9] Achievements in Renewable Energy - As of September 2025, China's installed capacity for wind and solar power reached 1.708 billion kilowatts, accounting for 46% of the total installed capacity [7] - In the first three quarters of this year, wind and solar power generation totaled 1.73 trillion kilowatt-hours, representing 22.3% of the total electricity consumption [7] AI Solutions for Energy Challenges - AI technologies, including deep learning and big data analysis, are being utilized to predict weather conditions, thereby improving the reliability of wind and solar power generation [7][12] - AI is transforming energy storage from a passive to an active role, optimizing charging and discharging strategies to mitigate issues like curtailment of wind and solar energy [7][9] Industry Collaboration and Innovation - The forum discussed the importance of cross-industry collaboration to build a new ecological environment in the energy sector, leveraging AI and other advanced tools [6][9] - Companies are adopting digital twin and AI models to enhance automation and efficiency in production processes, leading to improved product quality and reduced costs [8] New Energy System Development - The integration of large-scale renewable energy into the grid necessitates a fundamental transformation in energy system structure and management [9] - The development of a new energy system will involve diverse applications, including multi-energy complementarity and advanced energy scenarios [9] Challenges and Risks - Despite the benefits, the integration of AI in the energy sector faces challenges such as data security risks and algorithm reliability [12][13] - The global losses from AI security incidents are projected to rise significantly, highlighting the need for robust data protection measures [12] Future Directions - Experts suggest that a balanced approach between innovation and risk management is essential for maximizing the potential of AI in the energy sector [12][13] - Building a comprehensive data governance system and enhancing talent development are critical for the successful integration of AI technologies in energy operations [12][13]