Abstract
High temperature thermal energy storages are becoming more and more important as a key component in concentrating solar power plants. Packed bed storages represent an economically viable large scale energy storage solution. The present work deals with the analysis and optimization of a packed bed thermal energy storage. The influence of quasi-dynamic boundary conditions on the storage thermodynamic performance is evaluated. The Levelized Cost of Storage is innovatively applied to thermal energy storage design. A complete methodology to design packed bed thermal energy storage is proposed. In doing so, a comprehensive multi-objective optimization of an industrial scale packed bed is performed. The results show that quasi-dynamic boundary conditions lead to a reduction of around 5% of the storage thermal efficiency. Contrarily, the effect of the investigated design variables over the TES LCoS optimization is only slightly influenced by quasi-dynamic boundary conditions. Aspect ratio between 0.75 and 0.9 would maximize the storage thermal efficiency, while low preliminary efficiency around 0.47 would minimize the Levelized Cost of Storage. This work testifies that quasi-dynamic boundary conditions should be taken into considerations when optimizing thermal energy storage. The Levelized Cost of Storage could be also considered as a more reliable performance indicator for packed bed thermal energy storage, as it is less dependent on variable boundary conditions.
Highlights
The integration of thermal energy storage (TES) systems is key for the commercial viability of concentrating solar power (CSP) plants [1, 2]
Due to the inherent variability of the solar energy, the real working conditions of a TES in tegrated in a CSP plant are variable and the heat transfer fluid (HTF) mass flow rate will mainly depend on the actual DNI level
Including quasi-dynamic boundary conditions the optimal TES designs identified during multi-objective optimizations (MOO) A and MOO B do not overlap. These results suggest that when optimizing packed bed TES both ηth,ovr and Levelized Cost of Storage (LCoS) should be considered
Summary
The integration of thermal energy storage (TES) systems is key for the commercial viability of concentrating solar power (CSP) plants [1, 2]. Packed bed TES systems using natural rocks as sensible storage material and air as main heat transfer fluid (HTF) have been shown to be especially suitable for the generation of high-temperature CSP plants [3]. This tech nology can offer several advantages: (1) cheap and abundant storing material, (2) wide temperature range and high maximum temperature, (3) direct heat transfer between working HTF and storing material avoiding the need of an intermediate heat exchanger, (4) no chemical instability, degradation and corrosion and (5) low safety concerns [4]. Sensitivity studies, in which parameters are varied in a systematic way in order to identify their influence on some performance indicators, are rather common in previous literature These investigations assess the robustness of the solution algorithm used to model the TES thermal behavior. Nmat Nop NTES r T t TC Uw Vi VTES x between solids [W/(m∙K)] Mass flow rate [kg/s] Number of contact points on a semispherical surface of a single pebble Number of materials Number of operational years [y] Number of storage units Discount rate Temperature [K] Time [s] Thermocline [%] Overall heat transfer coefficient [W/(m2∙K)] Volume of materials [m3] Volume of the thermal energy storage [m3] Length [m]
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