期刊
APPLIED ENERGY
卷 285, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2020.116414
关键词
Biomass combustion; Combustion modeling; Emission reduction; Predictive control; Carbon monoxide
资金
- Climate and Energy Fund [853.606]
This paper presents the application of an emission limiting model-based predictive controller for a small-scale biomass grate furnace, extending the existing control system to improve combustion performance and minimize carbon monoxide emissions. Experimental results demonstrate a significant reduction in carbon monoxide emissions and improved control accuracy for supply water temperature, showing the robustness of the approach across different fuel types and water contents in the combustion process.
This paper presents the application of an emission limiting model-based predictive controller for a small-scale biomass grate furnace. The furnace has a nominal power of 100 kW with wood pellets as fuel, but it can be operated with different fuels as well. The model predictive approach extends the existing static feedforward controller of the investigated furnace with a dynamic feedback controller that is able to improve the combustion performance. Simultaneously, the formation of carbon monoxide emissions is minimized within the prediction horizon based on an available emission estimation model for pellets. The results obtained from closed-loop measurements show that the control concept is able to reduce carbon monoxide emissions in partial load operation up to four times while the control error of the supply water temperature for heating is nearly halved during transient operation. This is achieved by incorporating the emission estimation model into the constrained optimization of the predictive controller. Additional results obtained from closed-loop experiments for different fuel types with varying water contents demonstrate the advantages of the proposed model-based approach and its robustness with respect to typical uncertainties of the combustion process.
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