The document outlines a project to develop a smart boiler through introducing new measurement techniques to improve combustion, reduce emissions, and optimize performance for real-world use rather than just testing. Key steps included measuring air and fuel flow with new sensors, developing a new LoadCycleTest, and integrating components which showed emissions reductions of 47% for CO and 60% for OGC. The smart boiler is expected to provide improved real-life emissions performance and feedback to users.

2. 2
Outline
• Aim and scope of the Smart boiler project
• Process of the development phases – air and fuel
• Description of the type of sensors and the integration
• Introduction to LoadCycleTest
• Impact of fuel versus boiler
• Results of successful integration of components as basis for a smart boiler
– Including results showing reduction potential with the intelligent boiler
• Outlook, perspective and benefits from a smart boiler

3. 3
Aim and scope of the project
• Nationally funded by the Danish EPA
• Cooperation between NBE production and Danish Technological Institute(DTI)
• Research and development project
• Scope
– Development of a smart boiler by introducing a measurements techniques in the boiler for
improvement of the combustion, reduce the emissions and provide the user with a boiler
that is optimized for use and not for testing.

4. 4
Idea of the smart boiler

5. 5
Idea of the smart boiler – Information to the end-user

6. 6
Description of the development phases
1. Towards actual control of air
– Essential to be able to adapt the amount of air to the amount of fuel added
2. Measurement of added fuel
– Essential to know the actual mass of fuel in order to optimize combustion
3. Development and definition of a LoadCycleTest
– Development of boilers for use in real life

7. 7
Type of sensors and integration in the boiler - Air
• Venturi flow meter

8. 8
Type of sensors and integration in the boiler - Fuel
• Acustic technique for measurement of mass
Low load Low load Nominal load Nominal load

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Spring
Kenneth_85 Kongsgaden m mike
mtjell togmanden Gennemsnit
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LoadCycleTest - Why is it relevant?
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Kenneth_85 Kongsgaden m mike
mtjell togmanden Gennemsnit
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Kenneth_85 Kongsgaden m mike
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10. 10
LoadCycleTest
• Initially 24 h with 4 seasons included
• Next step 24 h testing per season(72h)
– Spring/Fall
– Summer
– Winter
• Stress test of system
• Realistic test of system performance
– Efficiency
– Emissions
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11. 11
Scientific results - Identification of correlation between fuel and emissions
As Ak Bs Bk Cs Ck Ds Dk Es Ek
N [mg/kg] 400 400 780 780 480 480 990 990 1180 1180
Calorific value [MJ/kg] 19,18 19,18 18,73 18,73 19,12 19,12 18,37 18,37 19,11 19,11
Ash content [%] 0,32 0,32 0,49 0,49 0,37 0,37 0,3 0,3 0,32 0,32
Prefix s – Skamol in burner
Prefix k – Ceramic in burner

12. 12
Impact of fuel versus boiler

13. 13
Results of successful integration of components as basis for a smart boiler

14. 14
Results of successful integration of components as basis for intelligent Boiler
Orginal boiler
Optimized boiler with air
mass measurment
Reduction
CO at 10% CO2 [mg/m3] 1313 702 47 %
OGC at 10% CO2 [mg/m3] 53 21 60 %

15. 15
• Results of successful integration of components as basis for a smart boiler
• Extra auger installed in burner
– More homogeneous amount of pellets to
the burner
– Next step ->mass of fuel as input for the system
• Further reduction potential
– By combining air and fuel mass
– Optimization of controller by use of LCT
– Air staging and adaption of air mass in different
load operations
• Special focus on NOx and dust reduction

16. 16
Outlook, perspective and benefits from a smart boiler
• Improved emissions during real life emissions
• Feedback to the user
– Active customer service
– Trouble shooting on the entire system
– Feedback on user-behavior of heating systems
– Service contracting
• Future possibilities
– New optimized algorithms can be added directly
– System can be extended to suggest improved overall heating system of the house
• Solar heat/power, heat storage, distribution to the house etc.
– Direct ordering of fuel based on data collected

17. 17
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