生物甲烷系统的能耗-绿色度两目标优化  

Bi-criteria optimization of biomethane production system considering energy consumption and environmental impact

作　　者：闫娜娜[1,2] 辛加余[2] 武斌[2] 鲍迪[2] 汪敬恒[1] 

机构地区：[1]郑州大学,化工与能源学院,河南郑州450001 [2]中国科学院过程工程研究所,离子液体与绿色工程研究部,北京100190

出　　处：《计算机与应用化学》2016年第4期445-451,共7页Computers and Applied Chemistry

基　　金：国家重点基础研究发展计划项目(2013CB733506)

摘　　要：针对生物质发酵制备生物甲烷这一复杂系统,本文以能耗和环境影响作为2个优化的目标函数,以温度、压力和回收率等为优化变量,并同时以质量守恒、能量守恒、技术选择和环境影响为约束条件,建立了两目标的混合整数非线性规划(MINLP)模型。其中,能耗目标以生产单位甲烷所需要消耗的能量为评价标准,环境影响目标则以生产单位甲烷的系统的绿色度为评价标准。同时,本文采用绿色度方法对低劣生物质和沼液沼渣的环境影响进行定量的分析和评价。针对这一复杂非线性优化问题,采用非支配排序遗传算法(NSGA-II)进行求解并得到系列Pareto优化解集。优化结果定量地揭示了各目标之间的权衡关系。同时,优化结果可为决策者提供有价值的参考和建议。A bi-criteria mixed integer non-linear programming （MINLP） model for the rigorous optimization of a complex bioruass to biomethane system through digestion is developed. The model simultaneously takes minimizing energy consumption and environmental impact as two optimization objectives and considers temperature, pressure, and recovery ratio, etc. as the optimized variables, subject to mass balance constraints, energy balance constraints, technology selection constraints, and environmental impact constraints. The energy consumption objective is measured by the energy consumption per Nm3 biomethane, and the environmental objectives measured by the green degree （GD） per Nm~ biomethane. Meanwhile, this paper quantitatively analyzes and evaluates the environmental impacts of biomass and digestate using the GD method. Finally, the complicated non-linear optimization problem is solved with nondominated sorting genetic algorithm II （NSGA-II） to obtain a set of Pareto optimal solutions. The result quantitatively indicates the tradeoff between the objective functions. Meanwhile, the Pareto optimal solutions can provide worthy insights and suggestions to decision makers.

关 键 词：混合整数非线性规划模型 超结构 绿色度 生物甲烷生产系统 

分 类 号：TQ015.9[化学工程] TP391.9[自动化与计算机技术—计算机应用技术]