Optimization, Based On Alumina Four-efficient Countercurrent Falling Film Evaporation System (exergy) Analysis

Evaporation is one of the important links of alumina production, and is also a crucial working procedure of energy consumption in the process of alumina production. Evaporation process is long and the influential factors of energy consumption are multiple, which are of serious coupling. The process parameters are adjusted empirically by the operators under the premise of stable production, so it's hard to realize the optimal operation, which leads to the high energy consumption in evaporation process.To solve this problem, a mechanism model is establishesd based on materiel balance, heat balance, phase balance and the equation of the speed of heat transporting by analyzing the mechanism of the four-effect refluent falling film evaporation system of an alumina plant. Through the exergy analysis based on the three-box analytical method to the evaporation system and each equipment, it comes to a conclude that the equipment losing exergy most is the second evaporator and the link losing exergy most is heat conduction exergy loss. An optimization model of energy consumption in evaporation process is developed to minimize the exergy loss percentage, in which the steam pressure, the degree of vacuum in the last evaporator, the material temperature, the total material flow and the material flow into the fourth evaporator are assumed to be variables, and the outlet concentration and production process are considered as constraints.The differential evolution algorithm(DEA) is chosen to solve the optimization model. Based on the problems that DEA is easy to lead to the local optimization and the operating factors and the evolution modes have a huge effect on the optimization performance, a method is proposed. It adopts self-adapting variation operator, self-adapting crossover operator and choosing different evolution modes in different evolution spaces. The improved DEA can keep the multiform of the colony and the strong global searching ability in the prophase of the whole searching process and the strong local searching ability and high convergence speed in the anaphase of the whole searching process. Four standard functions are taken to test its performance, and the simulation results demonstrate that the improved algorithm is feasible and effective.Finally, the improved EDA is applied to solve the optimization model of energy consumption in evaporation process. The energy consumption optimization of evaporation process is achieved.