多制冷站负荷分配调度策略研究

Research on Load Distribution Strategy for Multiple Refrigeration Plants

研究中央空调多制冷站冷源系统的负荷分配调度策略。利用制冷站实测数据,首先采用带指数遗忘的最小二乘法对制冷站的能耗模型进行参数辨识,建立多制冷站群控系统的能耗模型。在此基础上,以多制冷站系统能耗最低为目标,在满足末端冷负荷需求前提下,利用改进的野狗优化算法(Improved Dingo OptimizationAlgorithm,IDOA)优化了多制冷站负荷分配策略。在实际系统上进行的测试表明:提出的制冷站负荷优化控制策略较原运行方式在最大制冷季可单日节能8.88%,温差最大季可单日节能11.14%。

This paper studies the load distribution strategy of a central air conditioning multi refrigeration plant.Based on the measured data of the refrigeration plant,the least squares method with exponential forgetting is used to identify the energy consumption model parameters of the refrigeration plant,and then an energy consumption model of the multi refrigeration plant group control system is established.On this basis,with the goal of minimizing energy consumption in a multi refrigeration plant system and meeting the end cooling load demand,an Improved Dingo Optimization Algorithm(IDOA)is exploited to optimize the load distribution strategy for multiple refrigeration plants.The experiment conducted on an actual system shows that the proposed load optimization control strategy for refrigeration plants saved 8.88%energy compared to the original operation method during the maximum refrigeration season and 11.14%energy during the maximum temperature difference season.