Abstract
Thermal energy torage (TES) is a key enabling technology for the efficient exploitation of distributed generation systems based on renewable energy sources. Among the available options, research on latent heat TES (LHTES) solutions has been particularly active in the last decade, due to their ability to store and release high amounts of thermal energy in a very narrow temperature range. LHTES devices are based on phase change materials (PCMs), which act as thermal sinks or sources during their solid-to-liquid transition and vice-versa. As such, the development of reliable numerical tools for the prediction of the heat transfer and phase change characteristics of PCMs is of foremost importance, to help designing innovative and efficiently integrated LHTES implementations. In the present paper, the consolidated enthalpy-porosity (EP) method is compared to a novel lattice Boltzmann-phase field (LB-PF) algorithm in the simulation of a standard numerical benchmark for paraffin-like PCM melting problems. Performances and limitations of the two approaches are discussed, including the influence of model-related and purely numerical parameters. Outcomes from this study are used to confirm general guidelines for the application of well established methodologies, as well as to suggest new pathways for out-of-standard modeling techniques.
Highlights
In 2019, the share of renewable energy sources (RES) in gross final energy consumption was at 19.7% in the EU-27, which is very close to the 2020 EU target of 20 % [1]
The liquid fraction is computed at each iteration, based on an enthalpy balance, while the mushy zone is defined as a region where the liquid fraction lies between 0 and 1 and, at the same time, as a pseudo porous medium in which the porosity decreases from 1 to 0 as the material solidifies
Further refinements did not produce significant variations, so Grid #3 has been selected as the reference for all the subsequent simulations
Summary
In 2019, the share of renewable energy sources (RES) in gross final energy consumption was at 19.7% in the EU-27, which is very close to the 2020 EU target of 20 % [1]. For instance, had a 56.4% renewables share (with a 49% 2020 national target), compared to the 8.8% share of the Netherlands (with a 14% 2020 national target). A much higher effort is needed to increase the penetration of renewables and set the path towards the ambitious goal behind the European Green Deal - becoming the world’s first climate-neutral continent by 2050 [2]. To this aim, the integration of distributed RES technologies with thermal energy storage (TES) systems has proven to be an effective solution to both reduce the energy consumption and mitigate the inherent RES local intermittency. Recent examples of TES-based optimization of heating/cooling appliances for residential applications can be found in [4, 5]
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