Study On Robust Optimization And Control Of The Performance Of Entrained Flow Coal Gasification

In order to realize low carbonization using of coal, it must be promoted for the development of the new coal chemical industry based on coal gasification for it’s high carbon conversion and effective environmental protection. Entrained flow coal gasification technology will play an important role in the new coal chemical industry because of it’s advantages such as high adaptability to a wide range of coal types, high gasification efficiency and production load, and effective environmental protection. So it is important to study on the performance of the entrained flow coal gasification robust optimization and control, because it is significance to improve the efficient use of clean coal gasification and ensure coal gasification production economically, stably and safely.This research aims to realize the performance of coal gasification robust optimization for the entrained flow coal gasification production, that is, to optimize the performance and control the fluctuation as well. The typical entrained flow coal gasification technology-Shell coal gasification process was taken as the research background, and many advanced mathematical methods including Design of Experiment (DOE), statistical analysis, robust optimization and Statistical Process Control (SPC) were applied comprehensively in this dissertation. The main research purpose is to establish the theory and method that ascertaining a set of optimum controllable process parameters which can keep the performance of entrained flow coal gasification stable and optimizing as possible under the influence variety of random noise factors such as the fluctuation of moisture, ash or grain size of coal et al. This reassure will provide the instructions for the optimization operation and stable operation of entrained flow gasifier. In summary, the dissertation includes the following contents and contributions:1. The independent performance indexes of entrain flow coal gasification including CO%, H2%, gas yield and carbon conversion were chosen as the evaluation indexes. Shells coal gasification simulation model was founded with the Minimum of Gibbs Energy based on ChemCAD software. The model was verified by the experimental data of typical Shell gasification units SCGP-1. The verification results showed that the simulation model was accuracy.2. The analysis procedure of the robustness effect of the controllable process parameters on the performance of the entrained flow coal gasification based on Taguchi method was designed. The analysis method was founded using contrast to estimate the robustness effects of the controllable process parameters, half normal distribution to test the effects’ significances and the sensitivity to analysis the effects. Then the Shell gasification was taken as the example and analyzed by the above mentioned method.3. DRSM method was used to study on the performance of entrained flow coal gasification robust optimization. Double response surface models, mean-variances RSM models, about the controllable process parameters and the performance indexes of the gasification were founded. An improvement of loss function model was founded and applied to unite mean and variance of each gasification performance indexes into one robust evaluation index. A GA random search optimal algorithm was designed to solve the problem of the coal gasification performance robust optimization. For the indexes of the entrained flow coal gasification performance is multi-objects optimization, so 1-9 scale in Analytic Hierarchy Process (AHP) was used to evaluate the weight of each index, and the Desirability function was applied to integrate the indexes into one optimal object, GA random search optimization algorithm was used to search the optimal solution. Finally, according to the Shell gasification processes, the single objective robust optimal solution and multi-objective robust optimal solution were gained, and that of the certainty optimal solution were also gained to contrast. The contrasting results show that the proposed method about the entrained flow coal gasification performance of single objective robust optimization and multi-objective robust optimization can realize the robust optimization purposes.4. The demands of the coal gasification products have the characters of volatility, and JIT lean production mode is the advanced management to cope with the market demand fluctuation. The JIT lean production mode under the condition of the fluctuation demand for coal gasification production system was analyzed. Then the entrained coal gasification performance dynamic robust optimization while the entrained flow coal gasification implement JIT lean production was study, and the mathematical model was founded. The elitist optimizing strategy based on the principle of "Decomposition and Synthesis" was put forward. And then the optimization method based on nonlinear partial least-square was put forward. Finally, Shell coal gasification process system was analyzed, and the results show that the founded robust optimization method for the performance of the entrained flow coal gasification of the JIT lean production mode is feasible.5. Process Capability Index (PCI) was taken as the evaluation index to forecast evaluate the robustness of the performance of the entrained flow coal gasification, so as to examine the performance of coal gasification according to the optimal robust solution of the controllable operating conditions whether meet the production process requirement or downstream products production needs. Because coal gasification performance evaluation belong to multivariable process capability index (MPCI) evaluation, and currently MPCI is complex and difficultly application, a linear weighted MPCI based on the deviation model was put forward and simplex grid-point design method was adopted to get the weights. Then the method that the robustness performance of entrained flow coal gasification be forecast evaluated based on Monte Carlo simulation technique and with the linear weighted MPCI was proposed. Finally, Shell coal gasification was taken as the example and evaluated for the special optimal process parameters gained former study. The results show that the proposed method can forecast the performance robustness of entrained coal gasification process effectively.6. Statistical process control (SPC) technology was applied to monitor the production process performance of entrained coal gasification. A combined monitoring frame system for the performance of entrained coal gasification based on single variable SPC and multivariate MSPC jointed was constructed, which can inspect the situation of "out of control" and "instability". In allusion to the shortage of current SPC that alarm-omitted may occur, the MSPC based on PCA was adopted to validate the monitoring results. At the meanwhile, the traditional instability criterion in SPC is suitable for the distributed manufacturing system, while the entrained coal gasification belong to process industry, the performance monitoring needs on-line monitoring continuously. So an intelligent diagnosis model based on RBF neural network was developed for the entrain bed coal gasification performance statistics instability monitoring. Finally the application of the proposed monitoring method in Shell coal gasification proves the method can monitor the entrain bed gasification performance effectively and ensure the entrained gasification production stability.