Zhongtai: Rapidly increasing demand in the gas turbine market, focusing on the opportunity for domestic production of core components.

Zhongtai released a research report stating that the current surge in demand for gas turbines is driven by AI computing power, energy transition substitution, the urgent need for grid upgrades, supply-side mismatches, and the resonance of regional policies. Gas turbines, with their high efficiency, cleanliness, and flexibility, have become an important choice for upgrading energy in data centers, leading to a rapid increase in market demand. The current demand for gas turbines is in a rapid growth phase, with bottlenecks in high-end supply, comprehensive efforts in domestic substitution policies, and a recommendation to focus on occupying key positions in critical links and top-tier manufacturers with continuous technological moats. Key points from Zhongtai include: The irreplaceability of gas turbines lies in their stable, efficient, flexible, and clean core characteristics, which are particularly prominent in energy transition and high-load electricity scenarios. 1) Gas turbines have a short construction cycle, suitable for rapid deployment needs such as AI data centers, with a production and operation time of 12-18 months; 2) Quick start-up: "quick start-up" is one of the core design features of gas turbines, effectively mitigating the intermittency and fluctuations of wind power, solar power, and other new energy sources; 3) Stable power generation: Combined cycle gas turbine unit availability exceeds 95%; 4) Clean and low carbon, quick approval: carbon emissions are reduced by 60% compared to traditional coal-fired power stations. The current surge in demand for gas turbines is the result of AI computing power driving, energy transition substitution, the urgent need for grid upgrades, supply-side mismatches, and the resonance of regional policies. With the rapid development of artificial intelligence technology, the demand for computing power for large-scale model training and real-time inference continues to increase. Data center construction and expansion have accelerated, demanding more efficient, low-emission energy supply. Gas turbines, with their high efficiency, cleanliness, and flexibility, have become an important choice for upgrading energy in data centers, leading to a rapid increase in market demand. Backlog orders have been scheduled for production until 2028-2030 1) The current orders for the three giants have been scheduled until late 2028 to early 2029, operating at full capacity. Due to significant overlap among the three suppliers, even with an expansion demand, it is impossible to meet due to supplier capacity limits, resulting in no surplus capacity; 2) In terms of market share, the three companies collectively account for about 80% of heavy-duty gas turbine orders worldwide. Siemens and GEV each account for over 30%, while Mitsubishi accounts for about 20%. Companies like GE, Siemens, and others are still the major suppliers of light-duty gas turbines, with other small gas turbine manufacturers accounting for more than 10% and less than 20% of the global market share. Turbine blades are one of the most critical components in aircraft engines and gas turbines. Their main function is to continuously convert the energy of high-temperature, high-pressure gases in the combustion chamber into mechanical energy, thereby driving the engine rotation and other components. Therefore, turbine blades are subjected to extreme harsh working environments: high-pressure turbine blades need to rotate at high speeds of about 15,000 rpm under high temperatures ranging from about 1400C to 2200C and pressures of 20 to 50 standard atmospheres. The hub of the blades- the crucial part connecting the working blades with the turbine disc- bears centrifugal loads up to about 10,000 times the weight of the blades themselves, equivalent to a force of 10 to 15 tons. Risk warning: risks of AI computing industry development falling short of expectations; risks of gas turbine investment falling short of expectations; risks of uncertainties in national industrial policies; risks of overseas exports falling short of expectations; risks of underperformance by recommended targets; and risks of outdated data cited in the research report.