基于遗传算法热电冷联产系统多目标方案优化  

Multi-objective schematic optimization of CCHP with genetic algorithm

作　　者：王耀文[1] 黄锦涛[1] 李祥勇[1] 庄少欣[1] 肖彬[1] 

机构地区：[1]西安交通大学能源与动力工程学院,西安710049

出　　处：《沈阳工程学院学报（自然科学版）》2012年第1期26-29,共4页Journal of Shenyang Institute of Engineering:Natural Science

摘　　要：根据用户全年冷、热、电负荷设计冷热电三联产系统方案并实现优化运行是决定联产系统经济性的关键.建立了以一次能源节约率、净现值和CO2排放量为优化目标,以冷热电三联产系统中主要设备容量为决策变量的多目标优化模型,同时运用实数编码遗传算法进行优化计算,得到了"以电定热"和"以热定电"2种不同运行模式下的冷热电三联产系统优化设计方案.The economic performance of Combined Cooling ,Heating and Power（CCHP） system is determined by op- timum schematic design and operation strategy according to cooling, heating and electricity load of users. The paper es- tablishes multi-objective optimization model with primary energy saving ratio, net present value and carbon dioxide e- mission as objective function, main components capacities as decision variables. The optimal system schemes are gained by real-coded genetic algorithm under following electricity and following thermal operation strategy separately.

关 键 词：冷热电联产 多目标优化 遗传算法 实数编码 

分 类 号：TK019[动力工程及工程热物理]