Dynamic Characteristics And Model Predictive Control Study Of 130t/h Biomass Circulating Fluidized Bed Monolithic Unit With Variable Working Conditions

Biomass direct-fired power generation is one of the important ways to achieve large-scale utilization of biomass.Circulating fluidised bed boilers have the advantages of high fuel adaptability and load regulation capability,low pollutant emissions and low operating costs,making them one of the mainstream furnace types for biomass direct-fired power generation units at this stage.However,due to the variable fuel type,high water content,high alkali metal and chlorine content and low calorific value of the biomass fed into the furnace,problems such as poor combustion stability,high thermal load fluctuation and inadequate fuel combustion are likely to occur during the actual operation of the boiler,which may cause difficulties in ignition and fluidisation failure in serious cases,posing serious challenges to the safe and stable operation of the unit.Due to the constraints of safe production and operating economy,it has become an important technical tool to design,study and analyse the characteristics of the unit under various operating conditions through modelling and simulation.In this paper,a model of the steam and water system and turbine generator of a biomass circulating fluidised bed（BCFB）boiler is established based on the Modelica language,coupled with the combustion system to form the overall model of the unit.A study on the influence of material circulation multiplier,change of biomass fuel type,change of fuel water content on the unit and pollutant emission pattern is carried out.Based on the subspace identification method,the state space model of the unit under different operating conditions was obtained,and the model prediction controller（MPC）was designed and the control effect under the changing operating conditions was tested.The main findings are as follows:（1）A simulation model of a 130 t/h biomass circulating fluidised bed direct-fired power generation unit as a whole was established on the MWorks platform based on the Modelica language.The steam and water system was reasonably divided,and the feedwater system,coal saver,evaporation zone,superheater and turbine generator were modelled using the idea of collecting total parameters,and the physical parameters of the working mass were calculated using the IF97 formula.The accuracy and reasonableness of the established model were verified,and the overall error of the model was within 7%,and the longest dynamic time was about 5000 s for the step change of fuel quantity.（2）Appropriately increasing the cycle multiplier can lead to more uniform furnace chamber temperature,more adequate fuel combustion and lower pollutant emission levels.Dynamic tests were carried out on fuel type changes and moisture content changes,with four common biomass fuels used for comparison.It was found that the SO₂ emission concentration was higher for pine wood and corn straw at rated operating conditions,350.56 mg/Nm³ and 412.42mg/Nm³ respectively;the highest NO content in the flue gas was 199.47 mg/Nm³ for burning corn straw;the boiler operating conditions did not change much when changing from standard composite biomass fuel to pure corn straw fuel,and the overall operating conditions changed when changing to pure pine wood and pure cotton straw When changing from standard composite biomass fuels to pure corn straw fuels,the overall operating conditions change significantly,causing a large change in furnace chamber temperature.In addition to the fuel itself,the emissions of pollutants are strongly related to the furnace temperature,especially NO and chlorides.An increase in the water content of the fuel can seriously affect the combustion of the fuel,lowering the combustion temperature of the furnace chamber and thus changing the overall boiler operating conditions,and fuels with high water content may even have difficulties in ignition,making the boiler less efficient.（3）Based on the subspace identification method,the state space model of the unit at 100%operating conditions was obtained,and the Model Predictive Controller（MPC）was designed accordingly,and a comparative study was conducted on the control effect with the traditional PID controller.The MPC is found to be more advantageous in controlling a multivariable,large time lag and strongly coupled system such as the BCFB.The important parameters of the MPC controller were selected by comparison and tests were carried out for fuel quantity fluctuation and water content fluctuation.The control time for fuel quantity fluctuation was about 4000 s and for water content fluctuation was about 5000 s.The maximum dynamic deviation was 6.4%and the control effect was good.