The dairy farming industry is confronted with significant challenges regarding energy consumption and carbon emissions. Employing renewable energy sources is an efficient method to tackle these difficulties. However, the high initial capital costs (ICC) and carbon emissions with solar-coupled air source heat pump systems (SCASHPs) posed significant economic and environmental challenges, which remained major barriers to their application. Therefore, this study investigated the energy consumption of SCASHPs during 15 years using TRNSYS. Artificial neural network (ANN) and nondominated sorting genetic algorithm II (NSGA-II) were used to evaluate the environ-economic performance (life-cycle cost (LCC) and life-cycle climate performance (LCCP)) of heating systems under different design parameters (including the area of the solar collector (SC), the rated heating power, the volume of the heat storage tank (HST), and the start-stop temperature (SST) difference of the air source heat pump (ASHP)). The results indicated that the optimized SCASHPs achieved reduction of 12.5 % in ICC, a 7.86 % reduction in LCC, and a 9.48 % reduction in LCCP. This research delivered reliable optimization results and realized the lowest carbon emissions of the heating system, which provided a valuable reference for research and practice in related fields.

中文翻译：

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严寒地区奶牛舍太阳能耦合热泵加热系统的环境经济评价


奶牛养殖业在能源消耗和碳排放方面面临着重大挑战。使用可再生能源是解决这些困难的有效方法。然而，太阳能耦合空气源热泵系统 （SCASHP） 的高初始资本成本 （ICC） 和碳排放带来了重大的经济和环境挑战，这些挑战仍然是其应用的主要障碍。因此，本研究使用 TRNSYS 调查了 SCASHP 在 15 年内的能耗。采用人工神经网络 （ANN） 和非支配排序遗传算法 II （NSGA-II） 评价了不同设计参数（包括太阳能集热器面积 （SC）、额定加热功率、储热罐容积 （HST） 和空气源热泵 （ASHP） 的启停温度 （SST） 差值）下供热系统的环境经济性能 （生命周期成本 （LCC） 和生命周期气候性能 （LCCP））。结果表明，优化的 SCASHP 在 ICC 中降低了 12.5%，LCC 降低了 7.86%，LCCP 降低了 9.48%。该研究提供了可靠的优化结果，实现了供热系统的最低碳排放，为相关领域的研究和实践提供了有价值的参考。