27 May 24

Stratified water storage tanks

New study by Eurac Research on the development of an adaptive-grid model

  • English

Stratified water storage tanks play a pivotal role in thermal energy systems, in ensuring the effective balance between energy supply and heat demand for enhanced operational flexibility. As Eurac Research, we aim to enhance the computational efficiency of modeling these tanks for real-time control applications. In a recent scientific paper, published in the Journal Applied Thermal Engineering, our researchers introduce an adaptive-grid model that effectively captures the geometrical features of the tank, including inlet and outlet duct heights and dead volume sizes. This model also accurately represents the spatially discretized heat diffusion and characterizes the mixing effects within the inflow region, crucial for maintaining stratification. By addressing these aspects, the researchers facilitate better balancing of energy supply and heat demand, thereby enhancing operational flexibility in thermal energy systems.

The researchers conducted extensive activities to develop and validate the proposed model. Utilizing both TRNSYS and Modelica environments, they implemented the adaptive-grid model and conducted rigorous validation experiments. These experiments involved a hot water storage tank operating under various mass flow and temperature conditions, mimicking real-world scenarios encountered in heat pump-driven heating systems. Through these activities, they ensured that the model accurately reflects the dynamic behavior of stratified water storage tanks under diverse operating conditions.

"Our study contributes significantly to the existing body of knowledge by offering a practical solution to the computational challenges associated with modeling stratified water storage tanks. Compared to previous static-grid models, our adaptive-grid approach demonstrates a remarkable 55% reduction in simulation duration while maintaining the same level of accuracy. This reduction in computational effort is crucial for real-time control applications, where rapid decision-making is necessary to optimize energy utilization. Thus, our research provides an added value by offering a more efficient and accurate modeling tool for thermal energy systems, paving the way for enhanced operational performance and energy savings" says Jodeiri Khoshbaf Amir, first author of this study.

The original article can be read here

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