[SMM Hydrogen Energy Policy Update] National Development and Reform Commission (NDRC) and National Energy Administration: Implementation Opinions on Promoting the High-Quality Development of "AI+" Energy

On September 8, the National Development and Reform Commission (NDRC) and the National Energy Administration issued implementation opinions on promoting the high-quality development of "AI + energy."

AI + Power Grid:The document specifies that, in response to the requirements of grid security, new energy integration, and operational efficiency under the new-type power system, applications for power supply and demand forecasting, intelligent grid diagnostic analysis, and intelligent generation of planning solutions should be developed to enhance smart construction management of grid projects. It also calls for advancing multi-scale intelligent simulation analysis of the grid, exploring the application of AI models in intelligent decision-making and dispatch control, and improving the safe, reliable, and low-carbon operation of the generation-grid-load-storage system. Additionally, efforts should be made to steadily enhance the intelligent R&D of key equipment such as power transmission and transformation, promote predictive maintenance for power equipment, and develop intelligent health management systems with autonomous perception, decision-making, and execution capabilities to refine equipment management. Furthermore, intelligent integrated applications for marketing, distribution, and dispatch should be promoted to build a smart support system for grid operations and services, thereby improving the intelligent service level for customers throughout the power supply process. AI technologies should also be integrated into power emergency systems and capacity building to enhance the intelligent disaster prevention, mitigation, and relief capabilities of the power system.

Typical Application Scenarios of AI + Power Grid:

Intelligent Planning, Design, and Construction of Power Grids. Develop applications for intelligent power supply and demand forecasting, grid operation diagnostic analysis, intelligent decision-making for grid planning, and smart design of transmission and transformation facilities. Apply AI technologies to planning, design, and techno-economic analysis to drive the transformation of grid planning and design toward intelligence. Focus on construction-phase operation awareness and business monitoring, and build AI-powered applications for violation identification, progress simulation, online monitoring, real-time analysis of control indicators, and intelligent management of workflows to promote the intelligent upgrade of grid construction.

Grid Dispatch and Operation. Under the framework of a unified national power market, develop intelligent applications for new energy power forecasting, load forecasting, offline simulation analysis, online security analysis, extreme contingency response, dispatch decision support, market clearing optimization, and smart decision-making for power markets. Continuously improve the new-generation intelligent dispatch technical support system to ensure the safe and stable operation of the new-type power system.

Power Equipment Condition Assessment and Intelligent Maintenance. Develop applications for intelligent equipment condition monitoring and early warning, fault location and diagnosis, intelligent maintenance decision-making, disaster risk prediction, and automated work order generation to enhance the precision of equipment management.

Smart Operation Management of Distribution Grids. The application of technologies such as real-time perception, risk analysis, and intelligent decision-making for distribution grids will be established to comprehensively enhance the smart control capabilities and power supply reliability of distribution grids, while strengthening the coordinated regulation of generation-grid-load-storage at the distribution grid level.

Emergency Power Repair. Auxiliary decision-making systems for intelligent disaster risk early warning, damage assessment, and emergency response planning in power systems will be developed, promoting the intelligent application of emergency repair technologies and equipment to improve the disaster prevention, mitigation, and relief capabilities of power systems.

AI + New Energy Business Models:The document highlights that, to meet the demands of energy supply security and green low-carbon transition, AI technologies will be advanced in flexible regulation resources such as virtual power plants (including load aggregators), distributed ESS, and EV-grid interaction, enhancing load-side group control optimization and dynamic response capabilities. AI applications will be strengthened in the coordinated optimal dispatch of new-type energy storage and power systems, as well as in full life cycle safety, promoting intelligent optimization of renewable energy hydrogen production processes. AI will empower energy production processes in energy conservation and carbon emission management, improving the comprehensive energy efficiency and carbon reduction levels of multi-energy complementary integrated energy systems for electricity, heat, cooling, and gas supply. AI will be leveraged in zero-carbon parks, smart microgrids, and computing-power coordination to enhance the intelligent operation level of integrated generation-grid-load-storage systems and facilitate local consumption of new energy.

 Typical Application Scenarios of AI + New Energy Business Models:

Precision Control and Intelligent Operation of Virtual Power Plants.Virtual power plant operator platforms will intelligently optimize control strategies and generate control commands based on grid regulation instructions, market information, and dynamic changes in resource characteristics, enabling large-scale aggregation and optimal regulation of flexible resources and smart trading decisions for virtual power plants in electricity markets.

Intelligent Optimization of Green Hydrogen Production Processes.By integrating multi-dimensional data such as wind and solar power fluctuation forecasts, hydrogen storage tank capacity, electrolyzer temperature, and catalyst status, AI algorithms will dynamically optimize electrolyzer current density and establish an intelligent regulation system for the entire hydrogen production-storage-utilization chain, achieving millisecond-level matching between renewable power fluctuations and flexible electrolyzer loads.

Intelligent Carbon Reduction in Parks.Leveraging operational data from PV, ESS, and other equipment, the park’s intelligent carbon reduction coordination system dynamically optimizes energy dispatch strategies in real time, automatically adjusting air conditioning temperatures, charging pile power, and equipment start-stop sequences based on electricity prices and carbon emission factors. Through augmented reality visualization interfaces and voice assistants, personalized energy-saving recommendations are pushed to users, forming a smart "carbon-energy-cost" synergy model.

Intelligent Operation of New-Type Energy Storage.For the dynamic adaptation of new-type energy storage to power system dispatch, wide-area collaborative interaction, weak grid support, battery equipment safety monitoring, and equipment performance evaluation and maintenance, artificial intelligence technologies are employed to enhance the coordinated control capability of multi-type energy storage for weak grids. This establishes application systems for wide-area collaborative optimal control of renewable energy and co-located new-type energy storage, intelligent evaluation of ESS power stations, smart operation and maintenance decision support, and full life cycle safety, thereby improving the power supply guarantee capability of system-friendly renewable energy power stations.

Intelligent Marketing Services.For direct customer service scenarios such as oil, gas, and electricity, intelligent applications are developed, including intelligent assistance for agent business processing, smart customer service, intelligent generation of power supply plans, intelligent generation of comprehensive energy usage plans, smart dispatch of maintenance work orders, and diagnosis of user energy consumption anomalies. These efforts create an interactive, companion-style new customer service model, enhancing the intelligent service level throughout the entire customer process.