Moving grate furnaces have large diffusion as CHP plants due to economical feasibility and the ability to process low grade biomass fuels. Unfortunately, packed beds combustion is an high complexity combustion phenomenon and as result these plants are strongly affected by regulation issues which almost inhibit to successfully transfer results from numerical studies. However there is considerable margin to improve performances on pollutant emissions and efficiency by utilizing advanced regulation strategies. The most advanced control strategies adopt a model- based approach to deal with intrinsic high non linearity and complexity of the physics on packed bed combustion. In this paper data obtained from several experimental campaigns have been evaluated on the purpose to obtain an effective MIMO black box modeling of different furnace processes. Data are collected via a particular closed loop swinging regulation to exploit high frequency modal response of the furnace. The model used for parametric linear MIMO analysis utilize Finite Response Filters scheme applied on direct measured quantities or soft sensed ones. The resulting transfer functions from system identification procedures allow good prediction on local furnace behaviors and these can be utilized for synthesis of advanced controllers.
Amalfi, M., Palmieri, F., Gallucci, F., Guerriero, E. (2017). Mimo modelling of a moving grate furnace by finite impulse response filters. In European Biomass Conference and Exhibition Proceedings (pp.552-560). ETA-Florence Renewable Energies.
Mimo modelling of a moving grate furnace by finite impulse response filters
Amalfi M.;Palmieri F.;
2017-01-01
Abstract
Moving grate furnaces have large diffusion as CHP plants due to economical feasibility and the ability to process low grade biomass fuels. Unfortunately, packed beds combustion is an high complexity combustion phenomenon and as result these plants are strongly affected by regulation issues which almost inhibit to successfully transfer results from numerical studies. However there is considerable margin to improve performances on pollutant emissions and efficiency by utilizing advanced regulation strategies. The most advanced control strategies adopt a model- based approach to deal with intrinsic high non linearity and complexity of the physics on packed bed combustion. In this paper data obtained from several experimental campaigns have been evaluated on the purpose to obtain an effective MIMO black box modeling of different furnace processes. Data are collected via a particular closed loop swinging regulation to exploit high frequency modal response of the furnace. The model used for parametric linear MIMO analysis utilize Finite Response Filters scheme applied on direct measured quantities or soft sensed ones. The resulting transfer functions from system identification procedures allow good prediction on local furnace behaviors and these can be utilized for synthesis of advanced controllers.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.