Biomass and low-density polyethylene waste composites gasification: Orthogonal array design of Taguchi technique for analysis and optimization

http://manuscript.elsevier.com/S0360544222013846/pdf/S0360544222013846.pdf

Design and validation of reactant feeding control strategies for the solar-autothermal hybrid gasification of woody biomass

Abstract This paper presents the application of a Model Predictive Control (MPC) system to a solar-thermal reactor for carbon-steam gasification. The controller aimed at rejecting the disturbances in solar irradiation, caused by the presence of clouds, through the manipulation of the flow rates into the reactor. Simulations of a first-principles dynamic model were used to fit a linear, time-invariant model, to be used directly in the MPC algorithm. The MPC was tuned through simulations, until robust control was achieved. The proposed control system was compared to a fine-tuned multi-loop feedback control strategy. Simulations of the controlled reactor system showed that the linear MPC was capable of minimizing the effect of the disturbances within the entire operating region, outperforming a more conventional multi-loop feedback strategy. The results obtained suggest that the proposed controller is suitable for a real-world implementation.

Model Predictive Control of a Solar-Thermal Reactor

Fuel cell passenger car temperature tracking control based on cascade internal model control with nonlinear feedforward compensate

Catalytic gasification of rice hull by dielectric barrier discharge non-thermal plasma over potassium catalyst

Experimental assessment of woody biomass gasification in a hybridized solar powered reactor featuring direct and indirect heating modes

The present paper deals with both the modeling and the dynamic control of a solar hybrid thermochemical reactor designed to produce syngas through the high-temperature steam gasification of biomass. First, a model of the reactor based on the thermodynamic equilibrium is presented. The Cantera toolbox is used. Then, a model-based predictive controller (MPC) is proposed with the aim of maintaining the reactor’s temperature at its nominal value, thus preserving the reactor’s stability. This is completed by adjusting the mirrors’ defocusing factor or burning a part of the biomass to compensate for variations of direct normal irradiance (DNI) round the clock. This controller is compared to a reference controller, which is defined as a combination of a rule-based controller and an adaptive proportional–integral–derivative (PID) controller with optimized gains. The robustness of the MPC controller to forecast errors is also studied by testing different DNI forecasts: perfect forecasts, smart persistence forecasts and image-based forecasts. Because of a high optimization time, the Cantera function is replaced with a 2D interpolation function. The results show that (1) the developed MPC controller outperforms the reference controller, (2) the integration of image-based DNI forecasts produces lower root mean squared error (RMSE) values, and (3) the optimization time is significantly reduced thanks to the proposed interpolation function.

/pdf/model-based-predictive-control-of-a-solar-hybrid-3uhax05z.pdf

Model-Based Predictive Control of a Solar Hybrid Thermochemical Reactor for High-Temperature Steam Gasification of Biomass

/pdf/dynamic-simulation-of-a-solar-autothermal-hybridized-310yt7fr.pdf

Axel Curcio

Papers

Experimental assessment of woody biomass gasification in a hybridized solar powered reactor featuring direct and indirect heating modes

Model-Based Predictive Control of a Solar Hybrid Thermochemical Reactor for High-Temperature Steam Gasification of Biomass

Dynamic Simulation of a Solar-Autothermal Hybridized Gasifier: Model Principle, Experimental Validation and Parametric Study