Modeling Of Entrained Flow Gasification Process And Optimization Of Operation Parameters Considering Random Jump

In the process of gas gasification,the uncontrollable parameters such as coal feeding rate,ash content and moisture have important influence on gas production performance.The fluctuation of these uncontrollable parameters will lead to the decline of gas production quality and it is difficult to maintain the optimal value of coal gasification performance.It is beneficial to ensure the economical,safe and stable operation of gasification production to analyze and study the random jump fluctuation of uncontrollable parameters.Therefore,this paper considers the fluctuation of uncontrollable parameters in the gasification process,and constructs a jump diffusion model to describe the random fluctuation of uncontrollable parameters and the possible exceedance extreme value.On this basis,the operation parameters in the process of coal gasification are optimized to ensure the safe and stable operation of the gasification process and achieve the optimal gas production index.Under the influence of emergencies,uncontrollable parameters will appear beyond the limit and the parameter value will have “jump” fluctuation.A jump diffusion model is established to describe the dynamic change of uncontrollable parameters,so as to accurately describe the random fluctuation of these parameters and predict the possible exceedance extreme value in time.Based on the monitoring data of coal feeding speed,ash content and moisture,a jump diffusion model is established.Then,monte Carlo simulation is used to obtain simulated data,and the simulated data is compared with the real data to obtain Q-Q graph.The results show that the jump diffusion model can accurately simulate and predict the random fluctuation sequence of uncontrollable parameters and describe the random fluctuation process of uncontrollable parameters.In addition,in order to optimize the operation parameters of coal gasification process,a multi-objective stochastic optimization model was established,which took the jump diffusion model with uncontrollable parameters as constraint condition and the effective syngas volume fraction and cold gas efficiency as objective function.Finally,the multiobjective particle swarm optimization algorithm is used to solve the model and the Pareto curve is obtained.The decision maker can determine the value of the operating parameters based on the bias towards the two gas production objectives.