Sungrow Scientist Outlines 10 Trends for Clean Energy and AI Integration at Major Tech Conference

Sungrow Chief Scientist David Zhao Unveils 10 Trends Driving the Convergence of Clean Energy and AI at APSARA Conference

David Zhao, Senior Vice President and Chief Scientist of Sungrow Power Supply Co., Ltd., delivered a keynote address at the 2026 Apsara Conference in Hangzhou on September 23, outlining 10 technology trends shaping the integration of clean energy and artificial intelligence. Speaking at the three-day conference held from September 22-24 at the Hangzhou International Expo Center under the theme "Intelligence Goes Beyond," Zhao emphasized the symbiotic relationship between renewable power and AI computing.

"Clean energy gives AI the power it needs to thrive, while AI gives clean energy an intelligent brain. The two empower and complement each other," Zhao stated in his presentation titled "Clean Energy & AI: Powering A New Era."

Solar Overtakes Coal in China's Energy Mix

Zhao highlighted a significant milestone in China's energy transition, noting that by mid-year, the country's installed solar photovoltaic capacity had reached 1,286 GW. According to China's National Energy Administration, this figure represents approximately 31.5% of China's total installed power capacity and marks the first time solar has surpassed coal-fired power capacity of 1,285 TW as the nation's largest source of generation capacity.

By contrast, global installed capacity of electrochemical energy storage currently stands at just 700 GWh. Against estimated demand of 15 TWh by 2050, today's capacity represents only 5% of the projected requirement, indicating room for at least a nineteenfold increase in storage infrastructure.

Zhao projected rapid growth over the next five years across solar, wind, energy storage, electric vehicles and hydrogen technologies, alongside power supplies for AI data centers. Clean energy technologies centered on solar, wind, hydrogen and electric vehicles are expected to account for more than 60% of emissions reductions, while demand for clean energy could reach at least three to four times current installed capacity.

AI Computing Creates New Electricity Demand

The expansion of AI computing is generating substantial new electricity requirements. Research from China's National Energy Administration and firms including Wood Mackenzie project that China's data center electricity consumption will reach between 774-800 TWh by 2030, representing approximately 6% of national electricity demand and a nearly fivefold increase from about 170 TWh in 2025.

This surge in demand coincides with government policy requiring new data centers at designated computing hubs to obtain more than 80% of their electricity from renewable sources, part of China's broader strategy to reach peak carbon emissions by 2030. These dual requirements create simultaneous constraints on total electricity consumption, power density, bus voltage and the share of renewable electricity.

Three Major Technical Challenges

Zhao identified three critical challenges facing the integration of clean energy and AI infrastructure. The first concerns powering AI computing centers, where facilities could require hundreds of megawatts or even gigawatt-scale power while meeting stringent renewable energy mandates.

The second challenge involves solid-state transformers, which can directly convert 10 kV or 35 kV AC into 800V DC. Industry analysis shows these devices achieve conversion efficiencies above 97.5% while reducing footprint by 30-80% and weight by 50% compared to traditional transformers. However, the technology is still transitioning from demonstration projects toward large-scale commercial deployment.

The third challenge lies in four engineering barriers to applying AI to power electronics: a shortage of real-world fault data, the inability to rely entirely on AI for microsecond-level real-time control, risks associated with model extrapolation requiring hard limits based on physical constraints, and the lack of industry standards making accountability difficult when systems fail. Zhao called for joint development of explainable AI and industry standards to address these issues.

Ten Technology Trends

Focusing on power architecture, topology control, operating life and system coordination, Zhao outlined trends aimed at improving power efficiency, enabling smarter system design, enhancing operational reliability and better aligning computing with energy resources.

Key trends include shifting computing infrastructure toward renewable power sources to secure electricity prices of RMB 0.2–0.3 per kWh and reduce total ownership costs. DC architecture for AI computing centers is emerging as a new standard, with 800V DC systems targeting end-to-end efficiency exceeding 94%.

Zhao forecasted that solid-state transformers will move from demonstration projects to commercial deployment, with data centers serving as a key catalyst and 2027 potentially marking the start of widespread adoption. Grid-forming converters enabled by edge AI are expected to achieve penetration rates exceeding 40% by 2028 as grid-forming capability becomes increasingly common in tenders for renewable energy and AI facility grid connections.

Long-duration energy storage and multi-energy systems are set to become standard, with iron-air and iron-flow batteries supporting hundred-hour-scale storage, green hydrogen enabling seasonal energy storage, and natural gas paired with solid oxide fuel cells serving as backup for peak demand. Combined heat and power efficiency can exceed 90% in such configurations.

The final trend involves coordinated computing and power dispatch, where energy management systems would coordinate resources across three timescales—milliseconds to seconds, minutes to hours, and days to seasons—enabling GW-scale AI computing centers to shift from major electricity consumers to flexible, dispatchable assets providing frequency regulation, peak shaving and other grid services.

Product Development and Strategic Partnerships

On July 9, Sungrow launched EnerNeo, its first proprietary solid-state transformer. Built on an 800V DC architecture and equipped with SiC devices, EnerNeo delivers 99.999% availability, 98.5% system efficiency and a power density of 312 kW/m². The company signed strategic cooperation and procurement agreements with HEC Group and ZDATA, with commissioning of delivered SST products scheduled for the fourth quarter.

Sungrow, founded in 1997 in Hefei, China, by professor Cao Renxian, has grown to become the world's leading PV inverter supplier with cumulative installed capacity exceeding 740 GW by end of 2024, operating in over 180 countries. The company has collaborated with Alibaba Cloud since 2015 and in July this year jointly established the Green Token Joint Innovation Center to advance technological innovation and commercialization of lower-carbon computing infrastructure for AI data centers.

The company has proposed an "AI for ALL" system architecture built around source-load coordination, direct renewable power supply and coordinated computing and power, with applications spanning AI computing centers, large-scale renewable energy projects and virtual power plants.

Zhao concluded by describing power electronics as a bridge between clean energy and AI, aligning with Sungrow's mission to make clean power accessible while enabling energy systems to operate more efficiently and reliably. R&D personnel account for 41% of the company's workforce, while its power electronics equipment has helped reduce 670 million metric tons of CO₂ emissions globally.

The 2026 Apsara Conference, which began in 2009 and has evolved into Alibaba Cloud's flagship annual technology event, drew more than 120,000 attendees from over 70 countries to its 2025 edition. This year's conference featured more than 140 sub-forums across a 50,000-square-meter exhibition area, with Alibaba CEO Eddie Wu announcing plans to expand Alibaba Cloud's data-center capacity to more than 20 GW by 2032, a tenfold increase over 2022 levels.