The Research Of Modeling And Optimizing Of Biomass Power Generation Gasification Process

The development of "green energy" has become an important means in the industrialized countries of the world of cuting expenditure ,poducting new energy,converting crap to utilization and protecting the environment. The main reason for causing serious environmental pollution is the coal-dominated energy structure.The fossil fuels are non-renewable and the use of them can bring about environmental pollution,so the biomass occupied an important position in the renewable energy structure.Biomass gasification & power generation is an important form of biomass energy application,and biomass gasification process is the key of the technology of gasificaton & power generation.Although there have been some reports in this area at home and aboard,it is still very lack of the studies on modeling the characters of biomass gasification process and optimizing the parameters.So it has important theoretical and practical value, as well as environmental, social and economic benefits to study the modeling and optimization of the parameters about gasification process in the biomass gasification power generation system.Combined with the economic development of the energy situation and based on the analysis of the mechanism of the biomass power generation pyrolysis gasification process,we had made a systematical study to explore the modeling and optimization of the biomass gasification process, tar removal process,as well as the biomass solidification process.We also respectively establish a gasification process of the thermo-chemical balance mechanism model,the least squares support vector machine model,the artificial neural network model and dynamic model of circulating fluidized bed gasification,and do a simulation based on the experimental data on the models which we had already established.The results show that four of mathematical models of gasification process established in this paper has a good simulation effect, they also can effectively reflect the actual characteristics of the gasification process and verify the effectiveness and feasibility of the model.Based on the model, A multi-objective optimization objective function of gasification process had been made.The main objective is to solve that when the main performances and indexes of the gasification process (such as the gas content of effective components, gas calorific value, the efficiency of gasification, gas production rate, etc.) achieve the best value, the conditons of adjustable parameters should be meet to the gasification process,that is the optimization target of control parameters. Through the verification based on the optimization calculation,we have achieved the optimization target values when the gasification indexes reach the optimum,and we validated the the legitimacy and effectiveness of the objective function.Targeting the biomass rice stalk,we use linestone as catalyst and cracking catalyse the tar which was pyrolysised from the target.We build the rice straw biomass gasification tar removal catalytic cracking process model by the least squares support vector machine model and optimize the model parameters through genetic algorithm.We also has gotten the best catalytic cracking temperature and gas residence time, making the highest rate of catalytic cracking tar.We made wood biomass as a target analysis so that we can thermally crack tar,and we can use genetic algorithms to optimize the model parameters that is based on the wood biomass gasification pyrolysis tar removal process model through the least-squares fitting method,then we got the best pyrolysis temperature and equivalence ratio,so that it is possible to make the tar content reach the minianum.Based on the least squares support vector machine model,we had established the model of the biomass sawdust Compression molding process and fit the Optimization Parameters objective function of the molding process . On the basis of the experimental data ,we verified the model and the Optimization objective function, the results showed that the model can better simulated the molding process properties. After the Optimization Calculation,we obtained the max target value of the adjustable control Parameters when the main Indicators of the sawdust molding process reached the best value.The main Innovation points of the article is as following:1.Four biomass gasification process model had been established,such as the thermo-chemical balance mechanism model,the least squares support vector machine model,the artificial neural network model and the dynamic model of circulating fluidized bed gasification.2.A multi-objective optimization objective function of the biomass gasification process had been made.3.The tar removal model of the biomass gasification process by Catalytic Cracking or Pyrolysis Cracking had been established.4.The tar removal Optimization objective function of the biomass gasification process had been made.5.The model of the biomass Compression molding process had been established.6.The Optimization objective function of the biomass Compression molding process had been made.