AI Model Helps Inventory China’s Wind and Solar Power Facilities

A group of researchers from Peking University and the DAMO Academy, under the Alibaba Group umbrella, recently published a comprehensive, high-precision inventory of wind power plants (WPPs) and solar photovoltaic (PV) facilities in China in the journal Nature. Published this week, the study provides a data-driven assessment of how interregional coordination can enhance the integration of renewable energy into China’s energy system—the world’s largest and fastest-growing renewable energy system.

The research team employed an artificial intelligence (AI) model to analyse high-resolution satellite imagery exceeding 7.56 terabytes in size. Using this AI model, the team identified and mapped 319,972 solar facilities and 91,609 wind turbines across 1,915 regions in China in 2022.

The dataset offers a bird’s-eye view of the national renewable energy landscape, according to Liu Yu, a professor in the Institute of Geoscience and Remote Sensing at Peking University and the study’s lead author.

Key findings show that expanding the geographic scope of coordination significantly enhances the effectiveness of wind and solar complementarity. The two facilities are complementary: PV generation peaks during the day, while wind often generates more at night. Accordingly, combining the two can smooth the variability of renewable energy in a given area.

The study models four strategies for integrating renewables, ranging from provincial-level integration to full national-level coordination. The results indicate that a nationally scalable interprovincial coordination approach is the most effective strategy.

In a system with 80 percent dispatchable flexibility, this approach could increase effective renewable energy penetration by 99.88 TWh, the study reports. This amount equates to 9.1 percent of the total solar and wind energy counted in the study and could meet national average electricity demand for roughly 120 hours. Importantly, the figure represents a substantial amount of clean “new” energy that would otherwise be curtailed due to production limits, without requiring additional generation capacity.

By leveraging AI to establish a robust data foundation, the study offers a measured pathway for China to integrate its abundant renewables more efficiently and accelerate its carbon neutrality targets.