Packed-bed Thermocline Testing Facility with Air as HTF for Sensible Thermal

Abstract

A CSP plant can include large thermal energy storage (TES), and thanks to it the electricity supply is possible for extended periods, even at night-time and it is not affected by short term variations due to clouds occurrence during the sunny time. This advantage over other renewable which does not count with storage of large capacity (wind and PV) provides high flexibility and dispatchability to CSP and makes it the key to have a renewable energy mix (Islam et al., 2018). Currently, the mainstream TES solutions are based on sensible heat storage (SHS) and use a molten salt mixture that are stored in a two tanks system, one tank devoted to hot salt and another to cold salt. However, compared to this system, an only one thermocline tank is about 35% cheaper (Gil et al., 2010). A thermocline tank usually contains a solid filler that occupy most of the total volume and, thus, contribute to reduce the global cost of the system. As fillers, cheap and locally available materials are normally employed. Natural materials such as sand or different kind of stones are common (Schlipf et al.,2014). They form a packed-bed through which a liquid or gas flows. This work focuses in an air-rock packed bed able to operate at maximum temperature over 700ºC. In a system of such characteristics and according to most of literature references, it is expected to find significant differences between air and solid temperature (Bayón and Rojas, 2013). Using the facility available at CIEMAT, named, ALTAYR, experimental methodologies have been devised and put in practice with the objective to differentially measure solid and air temperature. The general performance of the packed-bed tank has been also analyzed. The relevance of a deep understanding on this storage prototype behavior stands on the need of employing it as an experimental tool to: 1) study the effects of the main parameters which will be critical for an industrial-scale thermocline tank design, 2) validate numerical models developed to allow the analysis of a wide range of operation conditions, 3) study the goodness of different materials as storage media.