基于改进和声搜索的地铁通风策略优化

Optimization on Subway Ventilation Strategy Based on Improved Harmonic Search

中国城市轨道交通正处于快速建设中,进一步改善车站内环境并降低车站运行能耗成为实现轨道交通高质量发展的关键途径;其中,通风系统在地铁环控系统总能耗中占比17%;为了在兼顾站内空气品质与舒适性的同时,减小系统末端风机能耗,模拟分析了西安某地铁站的空调负荷,建立了负荷预测模型并计算目标送风量,采用改进多目标和声搜索算法优化逐时送风量;通过与传统运行策略对比分析发现,优化后站内温度有明显提升,并且与室外保持约4℃的温差,满足车站内乘客暂时的舒适需求,在维持站内CO_(2)浓度低于健康浓度限值的前提下,通风系统节能率达22.7%。

Urban rail transit is currently in a rapid construction in china,in order to further improve the station environment and reduce the station operation energy consumption,it has become a key way to achieve the high quality development of rail transit.Among them,the ventilation system accounts for 17%of the total energy consumption in the metro environmental control system.In order to balance air quality and comfort of stations,reduce the energy consumption of the system end fan,and simulate and analyze the air conditioning load of a subway station in Xi an.The load prediction model was established,and the target air supply volume was calculated.The improved multi-objective sound search algorithm was used to optimize the hourly air supply volume.Through comparison and analysis with the traditional operation strategy,the temperature inside the station is significantly increased after the optimization,and the temperature difference between the station and the outdoor is about 4℃,which meets the temporary thermal comfort needs of passengers in the station.it is a prerequisite to maintain CO_(2)concentration in the station below healthy concentration limits,the energy saving rate of the ventilation system reaches 22.7%.