智能大厦中央空调系统的最优能量管理

从系统工程的角度分析了智能大厦中央空调系统在运行过程中的能耗问题,建立了中央空调系统能耗模型,提出了中央空调系统的优化运行与节能管理方法.通过离线预测和在线优化计算,得到机组次日优化运行策略,包括机组负荷在一天内各个时段的最优分配、最优蓄冷量、最佳释冷时间等.在最优策略指导下进行在线控制,通过在线实时采集数据,利用基于遗传算法的周期自回归模型(PARM)进行动态短期空调冷负荷预测;利用改进随机编码遗传算法实现中央空调日运行模型的求解,得出中央空调设备优化运行策略.实例计算结果表明:用此方法可使中央空调系统节能达24.5%左右.

Optimum Energy Management of the Central Air-Conditioning System in Intelligent Buildings

An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day's cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.