Large Language Model for Integrated Hydropower, Wind and Solar Operations Launched in Chengdu

An intelligent large model designed for integrated hydropower, wind and solar clean energy bases was officially unveiled in Chengdu on 16 July. Led by Yalong River Hydropower Development Company under SDIC Group, this platform marks the first of its kind nationwide for large-scale multi-energy clean power hubs. Its launch signals a new phase featuring independent controllability, systematic coordination and enhanced operational efficiency for the digital transformation of gigawatt-scale clean energy bases in China.

The model draws support from the Lianghekou Power-Calculus Integration Demonstration Project, home to the country’s first high-altitude cave-based intelligent computing centre. Full independent control is secured across computing infrastructure, foundational large model frameworks and algorithm architectures. 

It connects four core operational segments: forecasting and early warning, power dispatching, production management and electricity market trading. 

Massive heterogeneous data streams, including satellite remote sensing outputs, ground meteorological stations, watershed hydrological monitoring sites and wind-solar power stations, are consolidated to build an integrated forecasting system covering the whole river basin across all elements, scales and operational links.

The valid forecast horizon for watershed runoff has been extended from more than ten days under traditional approaches to 60 days. Hourly forecast accuracy within the initial ten-day window rises by 3 to 5 percentage points, while meteorological prediction speeds improve from hourly to minute-level updates.

For power dispatching, a multi-agent collaborative framework enables coordinated tuning of operational parameters across cascade reservoirs, wind farms and photovoltaic installations throughout the basin. 

This delivers precise alignment between flexible hydropower regulation capacity and fluctuating output from renewable power assets. Within production workflows, real-time artificial intelligence diagnostics monitor tens of thousands of units, transformers and inverters spread across the basin. 

The fault identification accuracy for photovoltaic modules exceeds 96 per cent, and fault localisation efficiency improves by 50 per cent, laying groundwork for gradual implementation of minimally staffed and unattended remote operation at outlying power stations.

On market trading fronts, the system delivers round-the-clock assessment of power market dynamics. Prediction accuracy for spot electricity prices lifts by over 10 per cent, and commercial decision-making can now be completed within minutes.

SDIC Group will continue unlocking the potential of integrated artificial intelligence and clean energy development. Mature technologies and standardised solutions will be rolled out to support intelligent upgrading at clean energy bases nationwide. Further progress will be pursued through industry-academia-research collaboration and targeted technological research.

Work will advance to generate original technical outcomes and develop first-of-a-kind major equipment in areas including intelligent construction and maintenance, integrated power operation and consumption, green hydrogen, ammonia and alcohol production, and advanced energy hardware.