Thermal energy storage (TES) is one of the key technologies for enabling a higher deployment of renewable energy. In this context, the present study analyzes the modeling strategies of one of the most common TES systems: stratified thermal storage tanks. These systems are essential to many solar thermal installations and heat pumps, among other clean energy technologies. Three different one-dimensional tank models are compared by their computing speed and resilience to long time steps. Two of the models analyzed are numerical, one being explicit and the other one implicit, and the other is analytical. The models are validated against data from experiments carried out considering small-scale stratified tanks, showing that their performance can be improved by using the Advanced Flowrate Distribution (AFD) method. The results show that the analytical model maintains its accuracy with longer time steps and is robust against divergence. Conversely, the numerical models show equivalent performance for short time steps, while the computation time is reduced. Although the AFD method shows promising results by achieving an improvement of 43% in terms of Dynamic Time Warping, its parameter optimization must be generalized for different tank designs, flow rates, and temperatures.

中文翻译：

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分层热储罐的瞬态建模：一维模型与高级流量分布方法的比较


热能存储（TES）是实现可再生能源更高程度部署的关键技术之一。在此背景下，本研究分析了最常见的 TES 系统之一：分层储热罐的建模策略。这些系统对于许多太阳能热装置和热泵以及其他清洁能源技术至关重要。比较了三种不同的一维坦克模型的计算速度和对长时间步长的适应能力。所分析的模型有两种是数值模型，一种是显式模型，另一种是隐式模型，另一种是解析模型。这些模型根据小型分层储罐实验数据进行了验证，表明可以通过使用高级流量分布 (AFD) 方法来提高其性能。结果表明，分析模型在较长的时间步长下仍保持其准确性，并且对发散具有鲁棒性。相反，数值模型在短时间步长下显示出相同的性能，同时减少了计算时间。尽管 AFD 方法在动态时间规整方面取得了 43% 的改进，显示出可喜的结果，但其参数优化必须针对不同的储罐设计、流速和温度进行推广。