首页> 外文会议>Proceedings of the 10th International Building Performancs Simulation Association Conference and Exhibition >DEVELOPMENT OF FAST CALCULATION METHOD FOR AMMONIA REFRIGERATION CYCLE AND PARAMETER ADJUSTMENT WITH GENETIC ALGORITHM
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DEVELOPMENT OF FAST CALCULATION METHOD FOR AMMONIA REFRIGERATION CYCLE AND PARAMETER ADJUSTMENT WITH GENETIC ALGORITHM

机译:遗传算法的氨制冷循环快速计算与参数调整

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A parameter adjustment method for an ammonia heat pump chiller using a genetic algorithm (GA) was developed. The parameters were automatically adjusted by the data of performance at rated point. Upon using the proposed adjustment method for parameters, output values of the simulation model agreed quite well with the performance data at rated point. The deviation of output was less than 1.2 [%] from the rated value. To speed up the adjustment process, a new approximation method with neural network was also proposed. This method decreases the calculation time required in obtaining refrigerant thermodynamic properties. The time required to calculate saturated and other refrigerant states were decreased by 14 times and 33 times respectively, while the average relative error was less than 0.04 [%] and 0.5 [%] when compared to the exact solution from REFPROP. The time required to calculate the refrigerant cycle decreased 20 times, while relative error was within 3 [%].
机译:开发了一种采用遗传算法的氨热泵冷水机参数调整方法。参数是根据额定点的性能数据自动调整的。使用建议的参数调整方法后,仿真模型的输出值与额定点的性能数据非常吻合。输出与额定值的偏差小于1.2 [%]。为了加快调整过程,还提出了一种新的神经网络逼近方法。该方法减少了获得制冷剂热力学性质所需的计算时间。计算饱和状态和其他制冷剂状态所需的时间分别减少了14倍和33倍,而与REFPROP的精确解决方案相比,平均相对误差分别小于0.04 [%]和0.5 [%]。计算制冷剂循环所需的时间减少了20倍,而相对误差在3 [%]之内。

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