Optimal Control Of An Aluminum Evaporation Process Based On Energy Efficiency Analysis

The evaporation process is used to recycle the valuable materials, remove impurities contended in the mother liquor, and maintain water balance of the whole alumina production process. It is a key procedure and a high energy consumption procedure in the production of alumina. The quality of the mother liquor not only influences the alkaline powder consumption of the grinding and dissolution process, but also influences the stability of the whole alumina production process. Thus, it is essential to develop optimal control techniques for the evaporation process, under the existing equipment and the current procedure, such that the specific quality of the mother liquor is met with the highest energy efficiency. In addition, with the increasing resources crisis, energy crisis and competition pressure, optimal control of the evaporation process becomes more and more important in enhancing the productivity and energy efficiency of the whole alumina production process.The evaporation process is a long procedure, thus there is a long time delay in parameter measurement. Moreover, the relationships among the paremeters are highly nonlinear coupled. In addition, there are many uncertainties existed in the evaporation process, such as the fluctuation of the solution discharged from other processes and the scaring of the evaporators. Thus, the currently used manual control method usually leads to unacceptable product mother liquor and condensate, and excessive live steam consumption.Consider these problems arising in the study of the evaporation process; this dissertation takes a practical four-effect countercurrent alumina evaporation process as the research background. It focuses on the mother liquor concentration prediction, the energy consumption analysis and optimization, and the operation control of the process to achieve the optimal energy efficiency. The detailed content and the main contributions are arranged as follows. 1) Due to the long and complex working procedure, there is a large time delay in the measurement of the product mother liquor concentration. To deal with this problem, a least square support vector machine (LSSVM) based model is built to predict the product mother liquor concentration. Firstly, the independent component analysis method is used to extract the main information from the non-stationary process data. On this basis, LSSVM model is established to predict the concentration of the product mother liquor. Using the real data collected from the practical evaporation process, the experimental results show that the prediction precision satisfies the the measurement requirement of practical industrial process. Thus, the prediction result provides guidance for evaporation process operation.2) The key factors for evaluating the performance of the unit cannot be measured. Furthermore, there is no historical concentration data to use. To obtain these concentration values, a numerical calculation method based on robust estimation function is proposed. The proposed numerical calculation method contains two parts:one is the mechanistic model built on balance principle and cascading method; another part is the error correction model based on the robust estimation of the measurement error. In the error correction model, the result of the LSSVM predictive model and the collected data are used. The numerical calculation results are the bases of process energy consumption analysis.3) Since the evaporation process is a high energy consumption process, but the existing optimization problems arising in the study of evaporation process are either aimed at the product quality or purely designed for energy saving, thus an energy efficiency optimization model is built, in which both the product quality and the energy consumption are considered. To construct the optimization model, firstly, on the basis of the numerical calculation results, the energy efficiency and the cause of energy loss are analyzed using the exergy analysis method. Then, an optimization model, whose objective function aiming at minimizing exergy loss rate and maximizing the target exergy efficiency, is built. Solving this optimization model, the opertation parameter settings for optimal energy efficiency can be obtained. The optimization results of the practical industrial production demonstrate that the quality of the mother liquor is guaranteed. Moreover, the target exergy efficiency is increased by3.03%averagely.4) Both the error correction model and the energy consumption optimization model contain complex constraints. To solve the constrained optimization problems, a vortex motion based particle swarm optimization (VMPSO) algorithm is developed. Firstly, an infeasible degree function is constructed based on the information provided by infeasible solutions. The summation of all the infeasible degree function is then appended to the objective function to form an augment objective function. The VMPSO with self-organized characteristic is then developed to solve the approximate optimization problem. The optimization results of several benchmark functions demonstrate the advantage of the proposed optimization algorithm in finding the global optimum.5) To control the evaporation process, the dynamic behavior is investigated. Then, dynamic model in each of the evaporation vessels is established. The dynamic model is in the form of multiple time delays space model with unknown delays. Since the delays influence the behavior of the process and the control effect, thus the delays should first be estimated. For this, a time delay estimation method with multiple characteristic time points is proposed to determine the unknown time delays. The main characteristics of the proposed estimation method are that the cost function of the estimation problem measures the discrepancy between predicted and observed system output; the partial derivatives of this cost function can be computed by solving a set of auxiliary time-delay systems. Using the partial derivatives, the estimation problem is solved by trust region interior point technique effectively. Numerical simulations demonstrate the accuracy and effectiveness of the estimation method. By applying this method, the obtained dynamic system is satisfied.6) To deal with the problems of unacceptable product and high energy usage encountered in the control of evaporation process, an optimal control problem is studied. The aim of this optimal control problem is to follow the desired parameter settings and decrease the steam consumption. This optimal control problem is with both multiple delays and continuous inequality constraints. To solve this optimal control problem, the control is first approximated by a piecewise constant function using the control parameterization technique. Then the optimal control problem is solved effectively through solving a sequence of approximate optimization parameter selection problems subject to only boundedness constraints on decision variables. The developed optimal control method is used to study the problem arising in the evaporation process. The optimal control results obtained based on field data show that the steam comsumption is reduced and the operation parameter settings to achieve the optimal energy efficiency are followed.