Deep borehole heat exchangers (DBHEs) coupled with heat pump systems present a promising solution for building space heating. However, conventional heating systems have limited demand flexibility and ignored the potential of direct heating using DBHEs. Thus, this study proposed a hybrid DBHE heating system by integrating latent heat thermal energy storage (LHTES) and borehole direct heating (BDH), and evaluated its performance in terms of energy, exergy, economy, and flexibility. This work aimed to achieve a matching operation between the LHTES and the heat pump and quantify the performance improvement potential of the hybrid system. Firstly, a thermodynamic analysis was carried out based on a pilot project, showing that the seasonal performance factor (SPF) of the system can reach 4.3 under the high-temperature heat storage mode, with a 45.5% improvement in exergy efficiency. Based on the field-measured data, a transient model of the hybrid system was developed using TRNSYS and MATLAB. With the established model, the single and interactive impacts of multiple critical parameters on the system performance were explored. Subsequently, a multi-objective optimization was performed using artificial neural networks and a genetic algorithm by considering several scenarios with different geographical locations and electricity tariffs. The optimization results revealed a trade-off between the levelized cost of energy (LCOE) and the flexibility factor, both of which were highly sensitive to the tank volume of the LHTES. The case studies showed that the LCOE of the optimized hybrid system was decreased by up to 8.5%, while the SPF, exergy efficiency, and flexibility factor were improved by up to 20.3%, 3.0%, and 998.7% respectively, in comparison with the conventional system. Compared with the hybrid system without using LHTES, integrating LHTES led to a decrease in LCOE by up to 5.0% and an increase in SPF by up to 3.8%. This study demonstrated the potential of using such hybrid systems for building heating decarbonization.

中文翻译：

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潜热蓄热混合深埋管换热器供暖系统多方面性能分析与优化


深埋管换热器 (DBHE) 与热泵系统相结合，为建筑空间供暖提供了一种有前景的解决方案。然而，传统供暖系统的需求灵活性有限，并且忽视了使用 DBHE 直接供暖的潜力。因此，本研究提出了一种集成潜热热能储存（LHTES）和钻孔直接加热（BDH）的混合DBHE加热系统，并评估了其在能量、火用、经济性和灵活性方面的性能。这项工作旨在实现 LHTES 和热泵之间的匹配操作，并量化混合系统的性能改进潜力。首先，基于试点项目进行了热力学分析，表明系统在高温蓄热模式下的季节性能因子（SPF）可达4.3，火用效率提高了45.5%。基于现场测量数据，使用 TRNSYS 和 MATLAB 开发了混合系统的瞬态模型。通过建立的模型，探讨了多个关键参数对系统性能的单一和交互影响。随后，考虑不同地理位置和电价的几种场景，使用人工神经网络和遗传算法进行多目标优化。优化结果揭示了平准化能源成本 (LCOE) 和灵活性因子之间的权衡，这两者都对 LHTES 的储罐容量高度敏感。案例研究表明，优化后的混合系统LCOE较传统系统降低了8.5%，SPF、火用效率和灵活性系数分别提高了20.3%、3.0%和998.7%。常规系统。 与未使用 LHTES 的混合系统相比，集成 LHTES 导致 LCOE 降低高达 5.0%，SPF 提高高达 3.8%。这项研究证明了使用此类混合系统实现建筑供暖脱碳的潜力。