基于PSO算法的乙烯分离过程脱甲烷系统多目标优化

采用流程模拟软件Aspen Plus，根据乙烯装置脱甲烷系统实际工业数据，模拟不同操作参数下脱甲烷系统的运行状况，并进行灵敏度分析；在此基础上，结合响应面分析法建立脱甲烷系统的多目标优化模型，并采用自适应变异粒子群算法进行优化求解。结果表明，采用此算法优化后的操作参数可有效降低脱甲烷塔的能耗，并保证乙烯的收率，为脱甲烷系统优化设计和操作提供了一种有效的方法，同时也为其他分离过程的优化提供了理论依据。

Multi-Objective Optimization of the Demethanization System Based on PSO Algorithm

By using the process simulation software Aspen Plus with several sets of practical industrial data, operating conditions of demethanization system for ethylene production unit under different operating parameters were simulated, and the sensitive analysis was carried out. On this basis, a multi objective optimization model was built up by using RSM(Response surface methodology), and then was solved by an adaptive variation particle swarm optimization algorithm. The results showed that the energy consumption of the demethanizer could be effectively reduced and the yield of ethylene could be ensured under the operating conditions obtained by the proposed algorithm. The effective proposed optimization method for process design and operation to the system would be a practical optimization one being applicable to other separation process.