中国工程院院士武强用数据拆解：AI能解决我国能源3大核心问题

Core Insights - The AI + Energy Development Conference highlighted the critical role of AI in addressing challenges in both traditional and renewable energy sectors, emphasizing energy security as a primary concern in the current international landscape [1][3]. Traditional Energy - Coal remains a dominant energy source in China, accounting for 53.2% of primary energy consumption and 67% of primary energy production in 2024, with a coal output of 4.76 billion tons [4]. - The disparity between production and consumption percentages is attributed to the need for significant imports of crude oil (approximately 550 million tons) and natural gas (1.3 billion cubic meters), which inflate the consumption statistics [4]. - The coal industry faces challenges such as safety incidents, health risks, and low recovery rates, but AI technology can provide solutions by enabling "transparent geology" for better mining operations and reducing the need for underground workers [4]. Renewable Energy - Renewable energy, particularly wind and solar, is crucial for energy growth, with installed capacity expected to reach 1.6 billion kilowatts in 2024 and 3.6 billion kilowatts by 2035 [5]. - The conversion of installed capacity to actual electricity generation is essential, as merely increasing capacity without effective conversion leads to waste [5]. - AI is identified as a key enabler for optimizing various energy storage technologies and enhancing the flexibility of thermal power, which is vital for maximizing the utilization of renewable energy [5]. Energy Efficiency - Current energy efficiency in China is significantly lower than in the U.S., with 3.4 tons of standard coal required to generate $10,000 GDP compared to 1.7 tons in the U.S., indicating substantial room for improvement [6]. - Achieving U.S. levels of energy efficiency could allow China to meet future energy demands driven by GDP growth, highlighting the importance of energy efficiency in addressing future energy challenges [6].