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AI+Energy: National Energy Administration Releases 51 High-Value Scenarios
The National Energy Administration recently held a national “AI+” energy on-site promotion meeting, marking the integration of AI and energy entering the systematic advancement stage from pilot exploration. The release of the first batch of 51 high-value scenarios provides a clear implementation path for the industry.
Energy Infrastructure: The Foundation Supporting AI
In 2025, China’s energy sector provided a solid physical foundation for AI development:
- Ten-thousand-card-level intelligent computing clusters: 42 built
- Total computing center power consumption: 170 billion kWh
- Power system scale: World’s largest, providing stable energy supply for AI training
Without energy, there is no computing power; without computing power, there is no AI. This logic chain determines the two-way enabling relationship between energy and AI.
51 High-Value Scenarios: From Concept to Implementation
The first batch of scenarios released by the National Energy Administration covers multiple segments of the energy industry chain:
Generation Side
- Intelligent wind farms: AI predicts wind speed and power output, optimizing turbine dispatch
- PV intelligent O&M: Image recognition detects component faults, reducing inspection manpower
- Nuclear power intelligent monitoring: Real-time analysis of equipment operation data, warning of potential failures
Grid Side
- Intelligent dispatching systems: AI optimizes power distribution, improving grid stability
- Load forecasting: Predicting electricity demand based on multi-source data, reducing wind and solar curtailment
- Fault diagnosis: NLP analyzes grid operation logs, quickly locating fault root causes
User Side
- Intelligent electricity management: Automatically optimizing electricity usage strategies based on tariffs and demand
- Integrated energy services: AI coordinating multiple energy forms including electricity, heat, cooling, and gas
- Virtual power plants: Aggregating distributed resources to participate in electricity market trading
25 Enterprises Sign Open Initiative
At the promotion meeting, 25 energy enterprises signed the “Initiative on Open Energy Sector AI Application High-Value Scenarios,” with core content including:
- Scenario openness: Opening real business scenarios and data resources to AI technology enterprises
- Standard co-construction: Participating in developing technical standards and evaluation systems for AI+Energy
- Safety priority: Ensuring AI applications are safe and controllable in critical energy infrastructure
This cooperation model breaks down barriers between traditional energy enterprises and technology companies, forming a collaborative innovation mechanism of “energy enterprises provide scenarios + AI enterprises contribute technology.”
Two-Way Empowerment: The Symbiotic Relationship Between AI and Energy
How Energy Empowers AI
| Dimension | Specific Support |
|---|---|
| Computing guarantee | Large-scale stable power supply supports intelligent computing center operation |
| Cost optimization | New energy electricity prices in western regions as low as 0.2 RMB/kWh, reducing training costs |
| Green label | Increasing renewable energy share reduces AI training carbon footprint |
How AI Empowers Energy
| Dimension | Specific Application |
|---|---|
| Efficiency improvement | Power generation equipment utilization rate increases by 5-15% |
| Loss reduction | Grid line loss optimization, transmission and distribution efficiency improvement |
| Decision optimization | Electricity market trading strategies AI-ized, revenue improvement |
| Safety enhancement | Predictive maintenance reduces unplanned downtime |
International Comparison: Characteristics of China’s Path
Compared with other countries’ AI+Energy strategies, China’s path shows the following characteristics:
- Scale priority: Leveraging the vast power system for rapid large-scale deployment
- Scenario-driven: Starting from specific business scenarios rather than pure technology orientation
- Policy guidance: Government-led release of high-value scenario lists to guide resource allocation
- State capital participation: Major energy central enterprises directly participate, with strong execution
Investment and Industry Opportunities
Short-term Opportunities (1-2 years)
- Energy IoT devices: Surging demand for smart sensors and edge computing nodes
- Industry-specific models: Vertical large model training services for the energy sector
- System integration: Energy enterprise AI middle-platform construction needs
Medium-to-long-term Opportunities (3-5 years)
- Autonomous dispatching systems: AI replacing manual dispatching decisions
- New business models: Energy as a Service (EaaS) combined with AI
- Carbon asset management: AI optimizing carbon emission monitoring and trading
Key Challenges
Data Barriers
Energy sector data is highly sensitive, and data sharing across enterprises and segments faces obstacles.
Security Requirements
Energy is the lifeblood of the national economy. The safety and reliability requirements for AI systems far exceed general application scenarios.
Talent Gap
Compound talent that understands both energy business and AI technology is severely insufficient.
Conclusion
The 51 high-value scenarios released by the National Energy Administration mark the entry of AI+Energy into the systematic implementation stage. This is not simple technology superposition but a deep restructuring of the energy industry.
For practitioners, the AI-ization of the energy sector provides more solid and long-term business opportunities than consumer internet. Energy is a rigid demand, AI is leverage, and their combination will generate continuous value creation.
Which sub-sector of AI+Energy do you think has the most commercial potential? Share your views in the discussion area.