China carries out deep integration of energy + AI to promote green and low-carbon transformation
In recent years, as the global climate change problem becomes increasingly serious, China, as the world's largest energy consumer and carbon emitter, is actively exploring new paths for green and low-carbon transformation. Recently, the National Energy Administration and the Ministry of Science and Technology jointly issued the "Guiding Opinions on Promoting the Deep Integration of Energy and Artificial Intelligence", which clearly proposed to deeply integrate artificial intelligence (AI) technology into the entire chain of energy production, transmission, storage and consumption, and drive green and low-carbon development with scientific and technological innovation. The following is a review and analysis of popular topics and hot contents across the network in the past 10 days.
1. Policy background and goals
According to the "Guiding Opinions", by 2025, China will initially build an energy AI technology system to achieve a significant improvement in the level of intelligence of the energy system; by 2030, a mature energy AI industry chain will be formed to help achieve the goals of carbon peak and carbon neutrality. Key tasks include:
| Key areas | Specific measures | Expected goals |
|---|---|---|
| Energy production | AI optimizes forecasting and scheduling of wind power and photovoltaic power generation | Renewable energy consumption rate increases by 10% |
| Grid management | Intelligent scheduling and fault diagnosis | Power outage time is reduced by 30% |
| User side | Intelligent power management and demand response | Resident electricity costs are reduced by 15% |
2. Typical cases of technical application
1.Wind and Light Power Generation Prediction: State Grid piloted AI power prediction system in the northwest region, and the accuracy of wind power prediction has increased to 92%, reducing the loss of wind and light abandonment by more than 500 million yuan.
2.Smart grid dispatching: Southern Power Grid uses AI algorithms to achieve millisecond load balancing, reducing coal-fired power generation by 1.2 billion kilowatt-hours during the peak summer in 2023.
3.Comprehensive energy services: Huawei and Huaneng Group cooperate to build a "smart power plant". Through AI, it optimizes the operating parameters of coal-fired units, and the annual CO emission reduction of a single unit reaches 18,000 tons.
| Project name | Technical application | Emission reduction effect |
|---|---|---|
| Fengguang AI prediction system | Deep Learning + Meteorological Data | Annual carbon reduction of 2 million tons |
| Grid intelligent dispatching platform | Reinforcement learning algorithm | Save 3 billion kilowatt-hours of electricity every year |
| Smart power plant system | Digital Twin Technology | Coal consumption is reduced by 3.5% |
3. Industry response and expert opinions
Du Xiangwan, an academician of the Chinese Academy of Engineering, said: "AI technology can help energy systems achieve a fundamental transformation from 'source-to-load-moving' to 'source-to-load-interaction', and is expected to contribute about 15% of carbon emission reduction by 2030."
The latest report from the International Energy Agency (IEA) shows that the global AI market size in the energy sector will grow from US$12 billion in 2023 to US$52 billion in 2030, of which China's market share is expected to reach 35%.
4. Challenges and suggestions
Despite the broad prospects, energy AI integration still faces challenges such as data barriers and lack of standards. Expert advice:
1. Establish an energy data sharing platform to break the "data islands"
2. Accelerate the formulation of technical standards for AI in the energy field
3. Strengthen the training of compound talents, and add 20,000 new relevant professional talents every year
With the implementation of policies and technological breakthroughs, China is providing new solutions for global green transformation through the innovative model of "energy + AI". This deep integration will not only reshape the energy industry structure, but will also become a key engine for achieving the "dual carbon" goal.
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