Improvement of accuracy with uncertainty quantification in the simulation of a ground heat exchanger by combining model prediction and observation
Improvement of accuracy with uncertainty quantification in the simulation of a ground heat exchanger by combining model prediction and observation
复制标题
通过模型预测和观测相结合，提高地热交换器模拟中不确定性量化的精度
DOI：
10.1016/j.geothermics.2022.102611
复制
发表时间：
2023
期刊：
影响因子：
3.9
通讯作者：
Nagano Katsunori
中科院分区：
文献类型：
--
作者：
Shoji Yutaka;Katsura Takao;Nagano Katsunori
近年来，随着浅层地热作为一种可再生能源的开发利用，地下换热器的模拟研究成为热点。地下换热器模拟是浅层地热系统设计和控制的重要依据。到目前为止，已经提出了各种模型和参数估计方法来表示实际现象，然而，模型预测和实际值之间不可避免地会出现误差。因此，需要一种可以明确说明这种不确定性的方法。因此，在这项研究中，我们表明，数据同化的方法，模拟和观测相结合，更准确的状态估计和不确定性量化，可以应用于地下换热器模拟。为此，我们进行了原位瞬态加热实验，使用单孔换热器，我们同化的实际观测使用集合卡尔曼滤波器的再生模拟。资料同化试验结果表明，模式参数，土壤有效热导率从地质柱估算的1.19 W m− 1 K − 1修正为1.70 ± 0.05 W m− 1 K −1，并重现了热响应测试的标准估算值1.69 W m− 1 K − 1。此外，对于地热交换器入口/出口温度，没有数据同化的模拟产生了约2.0 K的最大误差，而数据同化的模拟产生了标准偏差为0.08 K的高度准确的状态估计。所提出的方法允许后验估计土壤性质的地下换热器系统安装没有热响应测试的操作数据，以及通过统计支持和不确定性量化模型和观测值之间的偏差的校正。
With the utilization of shallow geothermal heat as a renewable energy source in recent times, several studies have focused on ground heat exchanger simulation. Ground heat exchanger simulation is an important factor that contributes to the design and control of shallow geothermal systems. Thus far, various models and parameter estimation methods have been proposed to represent actual phenomena; however, errors inevitably occur between the model predictions and actual values. Hence, a method that can explicitly account for this uncertainty is desirable. Thus, in this study, we show that data assimilation—a method that combines simulation and observation for more accurate state estimation and uncertainty quantification—can be applied to ground heat exchanger simulation. To this end, we perform an in situ transient heating experiment using a single-borehole heat exchanger, and we assimilate the actual observations using an ensemble Kalman filter for a reproductive simulation. The results of the data assimilation experiment indicate that the model parameter, i.e., the soil effective thermal conductivity, is modified from 1.19 W m−1K−1estimated from the geologic column to 1.70 ± 0.05 W m−1K−1, and it reproduces the standard estimate of 1.69 W m−1K−1from the thermal response test. Further, for the ground heat exchanger inlet/outlet temperature, simulation without data assimilation yielded a maximum error of approximately 2.0 K, whereas simulation with data assimilation produced a highly accurate state estimate with a standard deviation of 0.08 K. The proposed method allows a posteriori estimation of soil properties from the operational data of ground heat exchanger systems installed without thermal response tests as well as the correction of deviations between the model and observation values through statistical support and uncertainty quantification.