基于遗传-蚁群混合算法的多层办公建筑节能优化设计

Energy-saving Optimization Design of Multi-Story Office Buildings Based on Genetic Ant Colony Hybrid Algorithm

为解决建筑工程设计中节能优化问题,以福建省南平工业园区科技创新产业园配套基础设施1#办公楼为研究对象,运用遗传-蚁群混合算法计算分析目标函数和1个制冷周期内建筑能耗动态变化过程。结果表明,在目标函数建筑能耗求解上,遗传-蚁群混合算法的效率最高,遗传算法的运行效率次之,蚂蚁群算法的运行效率最低,具有较好的收敛性和全局搜索能力;不同算法得到建筑能耗优化结果也不相同,建筑能耗优化结果按蚂蚁群算法、遗传算法和遗传-蚁群混合算法的顺序依次降低;基于遗传-蚁群混合算法表明:模型A的建筑能耗稳定在2274kWh,模型B的建筑能耗稳定在2240kWh,相对于模型A,在1个制冷周期内,模型B具有更低的能耗,因此,模型B在节能方面更具有优势。

To solve the energy-saving optimization problem in building engineering design,the supporting infrastructure of the Science and Technology Innovation Industrial Park in Nanping Industrial Park,Fujian Province,No.1 Office Building,was taken as the research object.The genetic ant colony hybrid algorithm was used to calculate and analyze the iterative process of building energy consumption and the dynamic change process of building energy consumption within one refrigeration cycle.The results show that in solving the objective function of building energy consumption,the genetic ant colony hybrid algorithm has the highest efficiency,followed by the genetic algorithm,and the ant colony algorithm has the lowest efficiency,with good convergence and global search ability:The optimization results of building energy consumption obtained by different algorithms are also different.The optimization results of building energy consumption decrease in order of ant colony algorithm,genetic algorithm,and genetic ant colony hybrid algorithm;Based on the genetic ant colony hybrid algorithm,it is shown that the building energy consumption of Model A is stable at 2274kWh,while that of Model B is stable at 2240kWh.Compared to Model A,Model Bhaslower energy consumption within onerefrigeration cyclethus,Model Bhas more advantages inenergy conservation.