燃煤电厂脱碳系统的模拟与多目标优化

Multi-objective optimization of using NSGA-Ⅱ in CO_2 capture system for coal-fired power plant

针对燃煤电厂脱碳系统余热浪费问题,提出了增加多级换热器MHeatX模块的改进设计以提高热量利用率。在保证CO_2捕获率为85%的前提下,可降低系统总公用工程消耗量48.39%。在此基础上,再应用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对脱碳系统的热能消耗和CO_2捕获率2个目标进行了同步优化,得到了碳捕获率和再沸器热负荷的最优Pareto解集。为了将优化结果应用于实际,本文采用模糊集方法求得最优妥协解,可使CO_2捕获率达到95.92%,再沸器负荷降至775.39 MW,为该工艺的优化操作提供了理论依据。

In order to reduce the heat waste and increase heat efficiency, a method is proposed to improve the traditional CO2 capture system for coal-fired power plant by adding a multistage heat exchanger. Based on the 85 % of CO2 capture rate, the utility consumption is depressed to the original 51.61 %. Multi-objective optimization of heat consumption and carbon dioxide capture rate is proposed instead of single object optimization. At first, the modified carbon dioxide removal system for coal-fired power plant is modeled using Aspen Plus. Multi-objective optimization using Non-dominated sorting genetic algorithm with elitist strategy （NSGA-II） was performed based on the Aspen Plus simulation and MATLAB. At last, the Pareto-optimal set for the two optimization objective of carbon dioxide capture rate and reboiler heat duty is obtained and the best compromise solution is achieved using a fuzzy decision-making process. Carbon dioxide capture rate reaches 95.92 %, reboiler heat duty reaches 775.39 MW, which provide a theoretical basis for process optimization.