以AI赋能筑牢能源转型“智能屏障”

Core Viewpoint - The integration of artificial intelligence (AI) and energy is a strategic approach to ensure energy security, promote green transformation, and cultivate new productive forces in China, especially under the "dual carbon" goals and the construction of a new energy system [1]. Policy Guidance - Since the 18th National Congress, significant achievements have been made in China's energy sector, but the challenges of ensuring safety, promoting transformation, and improving efficiency remain daunting. By 2025, China's total electricity consumption is expected to exceed 10 trillion kilowatt-hours, with an additional 370 million kilowatts of wind and solar power generation capacity [1]. - The National Development and Reform Commission and the National Energy Administration issued implementation opinions in September 2025 to outline a "timeline" and "roadmap" for the deep integration of AI and energy [1]. Practical Applications - AI empowerment spans the entire energy supply chain, significantly improving safety and efficiency. For instance, AI inspection systems in coal mining have increased safety hazard identification efficiency, reducing underground personnel by 25%. In thermal power generation, intelligent scheduling systems can reduce coal consumption by 0.8 grams per kilowatt-hour, leading to substantial CO2 emissions reductions [2]. - In Inner Mongolia, AI models have enhanced the utilization of renewable energy, addressing the issue of green electricity being generated but not transmitted effectively. The digital twin grid in Shenzhen has minimized fault repair times through virtual mapping and intelligent warnings [2]. Competitive Advantage - China's energy intelligent transformation possesses unique competitive advantages, with over 80% of international oil and gas companies already investing in energy digitalization. The country has a vast energy market and diverse application scenarios, with the AI industry expected to exceed 7 trillion yuan by 2024 [3][4]. Challenges and Solutions - Despite initial successes, the integration of AI and energy faces multiple challenges, including the "black box" nature of large models affecting reliability in critical areas, data sharing difficulties due to inconsistent standards, and a shortage of talent proficient in both energy systems and AI algorithms [4]. - Addressing these issues requires collaboration among policies, enterprises, and research institutions to innovate mechanisms and break down barriers [4]. Future Outlook - The integration of AI and energy is not just a technological application but a crucial indicator of the core competitiveness of the energy industry. It transforms wind and solar power from being unpredictable to controllable and shifts the grid from passive to proactive management [5].