空调冷站群控方法研究

Research on Group Control of Air Conditioning Refrigeration Station

通过建立冷水机组和冷冻水泵的数学模型,并运用遗传算法对冷水机组和冷冻水泵的运行参数进行寻优,降低了空调冷站整体运行能耗。研究发现,在冷站监测数据有限的条件下,采用黑箱模型建立冷水机组的数学模型更有效,采用神经网络模型建立了冷水机组和冷冻水泵的数学模型,模型R^(2)均达到68%以上;启发式算法在进行多参数优化中效果显著,利用遗传算法对冷水机组和冷冻水泵的运行参数进行综合寻优,使冷水机组与冷冻水泵总功耗降低13.4%。此研究结论为空调冷站节能运行,提供了一种新的控制方法。

In this paper,the mathematical model of chiller and chilled water pump is established,and the operation parameters of chiller and chilled water pump are optimized by using genetic algorithm,so as to reduce the overall operation energy consumption of air conditioning cold station.It is found that the black box model is more effective to establish the mathematical model of chiller under the condition of limited monitoring data of cooling station.In this paper,the neural network model is used to establish the mathematical model of chiller and chilled water pump,and the R^(2) of the model is more than 68%.The heuristic algorithm is more effective in multi parameter optimization.In this paper,the genetic algorithm is used to optimize the parameter of the chiller and chilled water pump.Through comprehensive optimization of pump operation parameters,the total power consumption of chiller and chilled water pump is reduced by 13.4%.This study provides a new control method for energy-saving operation of air-conditioning cold station.