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Caldera inteligente: optimización de la combustión y reducción de emisiones

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Presentación realizada por Morten Gotlieb, Jefe sección Biomasa y Tecnología Combustión en el Instituto Tecnológico Danés, en el 11 Congreso Internacional de Bioenergía "Bioenergía 4.0: Retos y Oportunidades" www.congresobioenergia.org

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Caldera inteligente: optimización de la combustión y reducción de emisiones

  1. 1. 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
  2. 2. 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.
  3. 3. 4 Idea of the smart boiler
  4. 4. 5 Idea of the smart boiler – Information to the end-user
  5. 5. 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
  6. 6. 7 Type of sensors and integration in the boiler - Air • Venturi flow meter
  7. 7. 8 Type of sensors and integration in the boiler - Fuel • Acustic technique for measurement of mass Low load Low load Nominal load Nominal load
  8. 8. 0,00 2,00 4,00 6,00 8,00 10,00 12,00 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 kW TID Spring Kenneth_85 Kongsgaden m mike mtjell togmanden Gennemsnit 9 LoadCycleTest - Why is it relevant? 0,00 2,00 4,00 6,00 8,00 10,00 12,00 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 kW TIME Summer Kenneth_85 Kongsgaden m mike mtjell togmanden Gennemsnit 0,00 2,00 4,00 6,00 8,00 10,00 12,00 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 kW TID Fall Kenneth_85 Kongsgaden m mike mtjell togmanden Gennemsnit 0,00 2,00 4,00 6,00 8,00 10,00 12,00 0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36 0:00 kW TIME Winter Kenneth_85 Kongsgaden m mike mtjell togmanden Gennemsnit
  9. 9. 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 0% 20% 40% 60% 80% 100% 0 2 4 6 8 10 12 14 16 18 20 22 24 Poweroutputsetpoint Hours 24h 24h
  10. 10. 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
  11. 11. 12 Impact of fuel versus boiler
  12. 12. 13 Results of successful integration of components as basis for a smart boiler
  13. 13. 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 %
  14. 14. 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
  15. 15. 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
  16. 16. 17 • • •

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