SUPCON has successfully delivered the Green Power Dispatch Optimization Project for Datang Inner Mongolia Duolun Coal Chemical Co., Ltd., China’s first large-scale multi-energy dispatch optimization system integrating coal-fired power with renewable energy.

Powered by SUPCON’s Time-Series Pre-Trained Transformer (TPT) large model, the solution combines AI analytics and mechanism-based modeling to coordinate thermal power, renewables, energy storage, and coal chemical processes.

Through real-time sensing, forecasting, optimization, and closed-loop control, it improves source-grid-load-storage coordination and supports low-carbon transformation in coal chemical operations.

Exploring a Low-Carbon Path for Coal Chemical Operations

As one of China Datang Corporation’s first large-scale coal chemical enterprises, Datang Duolun Coal Chemical is accelerating its shift toward diversified, high-end, and low-carbon development. A major challenge was balancing the volatility of renewable energy with the stable power supply required for continuous coal chemical production.

To address this, SUPCON developed an integrated dispatch and energy management platform powered by Industrial AI and multi-energy optimization. The platform connects green electricity with the plant’s self-owned thermal power system, enabling safer, more stable, and more cost-efficient energy use across complex operating scenarios.

TPT: The Intelligent Core Behind Multi-Energy Optimization

At the heart of the project is SUPCON’s TPT large model, trained on massive industrial time-series datasets and designed to enable intelligent prediction and autonomous optimization across multiple operating conditions.

The system operates through a three-layer “Prediction–Optimization–Control” mechanism:

• Accurate Forecasting: Multi-timescale scheduling models dynamically generate power generation plans and control strategies, enabling rapid response and coordinated energy dispatch.
• Dynamic Optimization: AI-based optimization continuously adjusts wind power output, grid power intake, thermal unit load distribution, and energy storage charging/discharging strategies in real time.
• Model-Driven Control: By combining AI with process mechanism models, the platform optimizes boiler and turbine efficiency, improving overall thermal power system flexibility and energy performance.

Delivering Safety, Efficiency, and Sustainability

The integrated energy management platform has enabled deep integration between renewable energy and large-scale coal chemical production, improving safety, operational stability, sustainability, and economic performance.

After implementation, Datang Duolun Coal Chemical is expected to achieve around 496.9 million kWh of annual green electricity substitution, replacing up to 87.5% of coal-fired generation capacity. This equals approximately 151,700 tons of standard coal saved and 419,400 tons of CO₂ emissions reduced each year.

By combining Industrial AI with green energy technologies, SUPCON is helping drive smarter, greener, and more sustainable transformation across the coal chemical industry.