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A data-based compact pipe model for district-heating-and-cooling networks with variable flow conditions
Energy and Buildings ( IF 6.6 ) Pub Date : 2025-01-16 , DOI: 10.1016/j.enbuild.2025.115321
Mengting Jiang, Michel Speetjens, Camilo Rindt, David Smeulders
Energy and Buildings ( IF 6.6 ) Pub Date : 2025-01-16 , DOI: 10.1016/j.enbuild.2025.115321
Mengting Jiang, Michel Speetjens, Camilo Rindt, David Smeulders
The present study develops a data-based compact model for the prediction of the fluid temperature evolution in district heating-and-cooling pipeline networks. This model is based on an existing “reduced-order model” by the authors obtained from reduction of the “full-order model” describing the spatio-temporal energy balance for each pipe segment to a semi-analytical input-output relation between the pipe outlet temperature and the pipe inlet and ground temperatures. The proposed model (denoted XROM) expands on the original reduced-order model by incorporating variable mass flux as an additional input and thus greatly increases its practical relevance. The XROM represents variable mass flux by step-wise switching between mass-flux levels and thereby induces a prediction error relative to the true full-order model evolution after each switching. Theoretical analysis rigorously demonstrates that this error always decays and the XROM invariably converges on the full-order model evolution and, consequently, affords the same prediction accuracy. Performance analyses reveal that prediction errors are restricted to short “convergence intervals” after each mass-flux switching and the XROM therefore can handle substantially faster operating schemes than the current ones based on hourly monitoring and control. Convergence intervals of O ( minutes ) are namely typically sufficient – and thus switching frequencies up to O ( minutes − 1 ) permissible during dynamic operation and control actions – for reliable predictions. Quantification of these convergence intervals by an easy-to-use empirical relation furthermore enables a priori determination of the conditions for reliable predictions. Moreover, the XROM can capture the full 3D system dynamics (provided incompressible flow and heat-transfer mechanisms depending linearly on temperature) versus the essentially 1D approximation of current compact pipe models yet at similar computational cost. These attributes advance (parts of) district heating and cooling networks demanding prediction accuracies beyond 1D as its primary application area. This makes the XROM complementary to said pipe models and thereby expands the modelling capabilities for handling the growing complexity of (next-generation) networks.
中文翻译:
基于数据的紧凑管道模型,用于具有可变流动条件的区域供热和制冷网络
本研究开发了一个基于数据的紧凑模型,用于预测区域供热和制冷管道网络中流体温度的变化。该模型基于作者现有的“降阶模型”,该模型将描述每个管段的时空能量平衡的“全阶模型”简化为管道出口温度与管道入口和地面温度之间的半解析输入输出关系。所提出的模型(表示为 XROM)通过加入可变质量通量作为附加输入,扩展了原始的降阶模型,从而大大提高了其实际相关性。XROM 通过在质量通量水平之间逐步切换来表示可变质量通量,因此在每次切换后会引起相对于真实全阶模型演变的预测误差。理论分析严格地证明,这个误差总是衰减的,XROM 总是收敛于全阶模型演化,因此,提供了相同的预测精度。性能分析表明,在每次质量通量切换后,预测误差仅限于较短的“收敛间隔”,因此 XROM 可以处理比当前基于每小时监测和控制的操作方案快得多的操作方案。O(分钟)的收敛间隔通常就足够了,因此在动态操作和控制操作期间允许的开关频率高达 O(分钟−1),以实现可靠的预测。通过易于使用的经验关系量化这些收敛区间,还可以先验地确定可靠预测的条件。 此外,XROM 可以捕获完整的 3D 系统动力学(提供不可压缩的流动和传热机制,具体取决于温度),而不是当前紧凑型管道模型的本质上是 1D 近似,但计算成本相似。这些属性推动了区域供热和制冷网络的(部分)发展,要求将 1D 以外的预测精度作为其主要应用领域。这使得 XROM 与所述管道模型互补,从而扩展了处理(下一代)网络日益增长的复杂性的建模能力。
更新日期:2025-01-16
中文翻译:
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基于数据的紧凑管道模型,用于具有可变流动条件的区域供热和制冷网络
本研究开发了一个基于数据的紧凑模型,用于预测区域供热和制冷管道网络中流体温度的变化。该模型基于作者现有的“降阶模型”,该模型将描述每个管段的时空能量平衡的“全阶模型”简化为管道出口温度与管道入口和地面温度之间的半解析输入输出关系。所提出的模型(表示为 XROM)通过加入可变质量通量作为附加输入,扩展了原始的降阶模型,从而大大提高了其实际相关性。XROM 通过在质量通量水平之间逐步切换来表示可变质量通量,因此在每次切换后会引起相对于真实全阶模型演变的预测误差。理论分析严格地证明,这个误差总是衰减的,XROM 总是收敛于全阶模型演化,因此,提供了相同的预测精度。性能分析表明,在每次质量通量切换后,预测误差仅限于较短的“收敛间隔”,因此 XROM 可以处理比当前基于每小时监测和控制的操作方案快得多的操作方案。O(分钟)的收敛间隔通常就足够了,因此在动态操作和控制操作期间允许的开关频率高达 O(分钟−1),以实现可靠的预测。通过易于使用的经验关系量化这些收敛区间,还可以先验地确定可靠预测的条件。 此外,XROM 可以捕获完整的 3D 系统动力学(提供不可压缩的流动和传热机制,具体取决于温度),而不是当前紧凑型管道模型的本质上是 1D 近似,但计算成本相似。这些属性推动了区域供热和制冷网络的(部分)发展,要求将 1D 以外的预测精度作为其主要应用领域。这使得 XROM 与所述管道模型互补,从而扩展了处理(下一代)网络日益增长的复杂性的建模能力。