Research On Modeling, Control And Optimization For Industrial Entrained Flow Coal Gasification Process

Gasification technology is being widely developed in the chemical and energy processes as a practical coal-utilizing technology using coal more efficiently and cleanly. Based on the mechanism models, research on gasification process modeling, control and optimization are conducted in this study. Thermal model and kinetic model are both established to give deep insiht of behaviors for the industrial entrained flow coal gasifier. Effects of feed coal composition and operating conditions on gasification performances have been investiged in light of the developed models. Dynamic models are set up to analyse the transient dynamic reponses and evaluate the effectivenesses of control structures. Furthermore, the operation optimization for the gasifier is carried out by using the proposed new intelligence alrorithm. All these provide a new technical guidance for optimization and control in the industrial gasification process. The main contents of this paper are summarized as follows:1. A novel three stage equilibrium model which can be used to predict carbon conversion, is developed for coal gasification on the basis of thermal equilibrium theory. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas phase reaction stage. Steam participation ratio expressed as a function of temperature is introduced to estimate carbon conversion by assuming that only part of the water produced in the pyrolysis and combustion stage is involved to react with the unburned carbon in the second stage. The model overcomes the shortcome of the troditional themal model which need a specified carbon conversion in advance. Model results show a high prediction accuracy compared with published experimental data and models found in literatures. Effects of the amount of element C, H, O and ash in dry coal on the performance of gasifier are investigated by means of changing H/C and O/C molar ratios and ash content. The simulation results show that at the same operating temperature, the syngas productivity and oxygen consumption increase with the O/C molar ratio. However, with the increase of H/C molar ratio, the syngas productivity increases slightly and oxygen consumption remains unchanged. The relative amount of element O in coal has a more significant effect on the performance of gasifier. The syngas productivity reduces and the oxygen consumption raises with the increase of ash content. The above simulation results indicate the effects of major constituents of coal, i.e. C, H, O and ash on the performance of gasifier should be concerned and operating parameters need be adjusted in the industrial operating to optimize the production process and enhance the economic benefits.2. Cosidering the gas-char heterogeneous reactions kinetics, a one-dimensional partition gasifier model is proposed by simplying the flow behaviours in coal gasifier. The gasifier is divided into pyrolysis-combustion zone and gasification zone along the flow direction. The pyrolysis-combustion zone is modeled using the stoichiometry method. Detailed investigation was carried out on the gasification reaction rates in the reduction zone. The particle swarm optimization technique is introduced in this paper to address the lack of heterogeneous reaction kinetic parameters based on the random pore model for the specific feed Shenfu coal, and the huge deviation of the industrial product gas composition from the theoretical composition at equilibrium state. With the evaluated optimum kinetic parameters, robust agreement is achieved between the model outputs and the industrial data. Since the materials recirculation is not considered by one dimensional model, an equivalent compartment model (CM) is presented using the Aspen Plus process simulator. The CM blocking is established based on gasifier flow field analysis, using a number of compartments. A simple configuration of these compartments involving material recirculation should be able to simulate the main flow and provide the temperature and gas component distributions. The model predictions exhibit good agreement with industrial data in the model validation. The influences of the oxygen-to-carbon ratio (ROC) and the coal slurry concentration on the gasification performance are discussed. According to the intended final use, however, choosing a reasonable ROC to obtain a higher efficient syngas yield and lower oxygen consumption can be flexible.3. A dynamic model derived from the steady state model mentioned above is constructed for evaluating different control structures based on the disturbances rejection capabilities. From the sensitivity analysis, the optimal oxygen to coal ratio is obtained. The selection of an appropriate control structure is the most important decision when designing gasification control systems. In industrial practice, the gasifier is controlled by gasifier temperature, which manipulates the oxygen to coal ratio. The temperature is controlled at a suitable value slightly higher than the melting temperature of feed coal so that the operation can accomplish the slag discharge target. Two control structures are studied. The first control structure (CS1) uses the coal feed rate as the throughput manipulator (TPM). The other control structure (CS2) uses the oxygen feed rate as the TPM. The dynamic responses for feed flow rate and composition disturbances are evaluated in the two control structures. Although both control structures can handle the disturbances and hold the gasification temperature very close to the specified value, the results show that the the CS2control structure solve the disturbance issues effectively with smaller deviations.4. Since entrained flow gasification is such widely used, even a slight improvement in the operation of the gasifier can increase the economic benefits significantly. Different goals are to be reached depending on the downstream demands. Hence the objective of the operation optimization of the gasification process is to maximize the yield rates of efficient syngas and the H2product rate as well as minimizing the oxygen consumption. However, the three optimization objectives cannot be achieved simultaneously because of conflicts between them. An Chaos self-adaptive multi-objective differential evolution (CSaDE) algorithm is proposed to solve this multi-objective problem. In order to overcome the problems of premature convergence and falling into the local optimum, a chaotic migrate operator is introduced to the SaDE algorithm to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on various benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Multi-objective optimization problem of an entrained flow coal gasifier is then solved using the proposed CSaDE algorithm. Many sets of operating conditions that will yield such an end result are provided. Operating under the conditions predicted will enhance productivity and reduce the consumption and thereby increase profit. Since the CSADE method is a general algorithm, the described procedure is suitable for maximizing the benefits of any operating industrial gasification plant.