South KoreaEnergy and utilities2026 – ongoingKorea East-West Power
Deep-learning coal-property prediction at Dangjin
Korea East-West Power reported about KRW7 billion in annual fuel savings after coal-property prediction
Problem
Dangjin operators needed timely information about fuel properties to adjust plant operation and limit efficiency losses.
Approach
Korea East-West Power deployed deep learning that analyzed fuel characteristics and operating data in real time. The system provided operating guidance at Dangjin units 5–10. The plant also installed an integrated thermal-performance monitoring system.
Results
Takeaway
Fuel predictions fed into operating guidance at working generating units. The company did not disclose how it calculated the annual savings.
Categories
- Size
- Large enterprise
- Industry
- Energy and utilities
- Business function
- Production and quality
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and ML
- Adoption
- Built in-house
- Evidence
- Company's own claim
Sources
Source summaries
The report described real-time coal-property prediction and operating guidance at Dangjin. It attributed about KRW7 billion in annual fuel-cost savings to application at units 5–10.
Full details are in the original sources.