A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy. (15th August 2019)

• Record Type: Journal Article
• Authors: Lago, Jesus; De Ridder, Fjo; Mazairac, Wiet; De Schutter, Bart
• Is Part Of: Applied energy. Volume 248(2019)
• Page Start: 640
• Page End: 655
• Publication Date: 2019-08-15
• Subjects: Thermal Storage -- Stratified Tank -- Modeling -- Parameter Estimation -- Optimal Control -- Numerical Optimization; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.04.139
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: We propose a smooth and continuous 1D model for stratified thermal storage vessels. The model includes buoyancy and mixing effects through a smooth formulation. The smoothness property is critical to integrate the model in optimization problems. The new model solves some computational issues of existing models from literature. Buoyancy is modeled by distinguishing between slow and fast buoyancy effects. Abstract: To mitigate the effects of the intermittent generation of renewable energy sources, reliable and efficient energy storage is critical. Since nearly 80% of households energy consumption is destined to water and space heating, thermal energy storage is particularly important. In this context, we propose and validate a new model for one of the most efficient heat storage systems: stratified thermal storage tanks. The novelty of the model is twofold: first, unlike the non-smooth models from the literature, it identifies the mixing and buoyancy dynamics using a smooth and continuous function. This smoothness property is critical to efficiently integrate thermal storage vessels in optimization and control problems. Second, unlike models from literature, it considers two types of buoyancy: slow, linked to naturally occurring buoyancy, and fast, associated with charging/discharging effects. As we show, this distinction is paramount to identify accurate models. To show the relevance of the model, we consider a real tank that can satisfy heat demands up to 100 kW. Using real data from this vessel, we validate the proposed model and show that the estimated parameters correctly identify the physical properties of the vessel. Then, we employ the model in a control problem where the vessel is operated to minimize the cost of providing a given heat demand and we compare the model performance against that of a non-smooth model from literature. We show that: (1) the smooth model obtains the best optimal solutions; (2) its computation costs are 100 times cheaper; (3) it is the best alternative for use in real-time model- based control strategies, e.g. model predictive control.