EA-SAS Boiler DIGITAL TWIN
Energy ON helps to stabilize biomass power plant efficiency through real-time control optimization with Digital Twin, which was created by
We are an official supplier of EA-SAS Boiler – Digital Twin of a biomass power plant that monitors, analyses, estimates efficiency, and controls the power plant 24/7 most efficiently by evaluating real-time data.
RESULTS
1. EXTEND TIME BETWEEN MAINTENANCE
​2. REDUCE FUEL CONSUMPTION UP TO 9 %
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​3. OPTIMAL CONTROL
24/7
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4. CHANGE OPERATION MODE WITHOUT LOSSES
Digital Twin setup: 6-month timeline, no extra hardware costs, compatible with multiple hardware types, ROI achievable within a year, user-friendly implementation and maintenance.
CHALLENGES
Biomass power plants typically operate 2-9% below their design efficiency limits.
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Human behavior and the limited capabilities of programmable logic controllers (PLCs) are the main reasons why biomass power plants operate at lower efficiency than designed.
Operators may not follow correct procedures or may lack sufficient knowledge, while the PLC logic cannot adapt to changing fuel moisture content, fuel quality, and real energy demand.
PROCESS OF DIGITAL TWIN
COLLECT DATA
All process data from control systems, SCADA, IoT being collected in the unified database
ESTIMATE
Advanced algorithms estimate power plant operation and provide set-point corrections
MONITOR
Understand power plant status in real-time
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SMART CONTROL
Optimal power plant control 24/7
CASE STUDIES
INDUSTRY: ENERGY PRODUCTION
TECHNOLOGY: BIOMASS CHP PLANT
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Helped to achieve fuel-saving targets previously agreed upon with the plant owner
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Optimized control of supplied fuel according to the fuel layer in the boiler for efficient combustion
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Maintenance planning and recommendations for further improvement and CAPEX optimization
INDUSTRY: PAPER MANUFACTURING
TECHNOLOGY: STEAM BOILER PLANT
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• Reduced biomass consumption - 2.9% (2700 MWh) in the first year
• EA-SAS Boiler allows tracking performance of each shift and maintains control quality
• Data-driven maintenance decisions prolonged duration between maintenance stops
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