Data-driven multi-objective optimization design of transcritical CO2 heat pump

doi:10.16085/j.issn.1000-6613.2019-1362

Abstract

Abstract:

In this paper, aiming at the problems of high cost and large space occupation of transcritical CO₂ heat pump, a data-driven multi-objective optimization design method of transcritical CO₂ heat pump based on economy and practicability was proposed. A large number of driving data were obtained by simulating the performance of a transcritical CO₂ heat pump, and then a thermodynamic prediction model of a transcritical CO₂ heat pump was constructed via a BP neural network. Moreover, the multi-objective optimization model of transcritical CO₂ heat pump was established from the perspectives of investment, operation, environment and space occupation. Finally, the total annual cost and tank volume that the residential users concern most with were used as optimization objectives. The optimal design scheme based on elite non-dominated sorting genetic algorithm (NSGA-Ⅱ) and TOPSIS decision method were then solved. The case study showed that the optimal solution for obtaining small space occupation and low total annual cost is tank volume of 0.235m³ and total annual cost of 958.1USD/a. By analyzing the influence of design parameters on the optimization objective, it was shown that the influence of the thickness of insulation is mainly concentrated in a better area, and the influence of the diameter and height of the tank is greater, while the influence of the temperature difference in gas cooler is smaller.

Key words: CO₂ heat pump, transcritical, multi-objective, space occupation, optimization

摘要：

针对跨临界CO₂热泵成本过高与占用空间大等问题，提出了一种基于经济性与实用性的数据驱动跨临界CO₂热泵多目标优化设计方法。本文通过对跨临界CO₂热泵进行性能模拟获得大量的驱动数据，然后经由BP神经网络构建跨临界CO₂热泵的热力学预测模型，并且从投资、运营、环境以及空间占用等多角度建立跨临界CO₂热泵的多目标优化模型。最后以住宅用户最关心的总年度成本与水箱容积为设计优化目标，通过精英策略非支配排序遗传算法（NSGA-Ⅱ）与TOPSIS决策法进行最优设计方案求解。案例研究表明，占用空间小、总年度成本低的最优设计方案的水箱体积为0.235m³、总年度成本为958.1USD/a。且通过分析设计参数对优化目标的影响，发现水箱保温层厚度的影响主要集中在一个较优区域，水箱直径与高度的影响较大，而气冷器换热温差的影响较小。

关键词: CO₂热泵, 跨临界, 多目标, 空间占用, 优化

CLC Number:

TB61

Enteng LI, Yingjie XU, Xiaodong XIE, Wei FAN. Data-driven multi-objective optimization design of transcritical CO₂ heat pump[J]. Chemical Industry and Engineering Progress, 2020, 39(5): 1657-1666.

李恩腾, 徐英杰, 谢小东, 范伟. 数据驱动的跨临界CO₂热泵多目标优化设计[J]. 化工进展, 2020, 39(5): 1657-1666.

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Data-driven multi-objective optimization design of transcritical CO₂ heat pump

数据驱动的跨临界CO₂热泵多目标优化设计

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