Abstract
Direct steam generation coupled is a promising solar-energy technology, which can reduce the growing dependency on fossil fuels. It has the potential to impact the power-generation sector as well as industrial sectors where significant quantities of process steam are required. Compared to conventional concentrated solar power systems, which use synthetic oils or molten salts as the heat transfer fluid, direct steam generation offers an opportunity to achieve higher steam temperatures in the Rankine power cycle and to reduce parasitic losses, thereby enabling improved thermal efficiencies. However, its practical implementation is associated with non-trivial challenges, which need to be addressed before such systems can become more economically competitive. Specifically, important thermal-energy processes take place during flow boiling, flow condensation and thermal-energy storage, which are highly complex, multi-scale and multi-physics in nature, and which involve phase-change, unsteady and turbulent multiphase flows in the presence of conjugate heat transfer. This paper reviews our current understanding and ability to predict these processes, and the knowledge that has been gained from experimental and computational efforts in the literature. In addition to conventional steam-Rankine cycles, the possibility of implementing organic Rankine cycle power blocks, which are relevant to lower operating temperature conditions, are also considered. This expands the focus beyond water as the working fluid, to include refrigerants also. In general, significant progress has been achieved in this space, yet there remain challenges in our capability to design and to operate high-performance and low-cost systems effectively and with confidence. Of interest are the flow regimes, heat transfer coefficients and pressure drops that are experienced during the thermal processes present in direct steam generation systems, including those occurring in the solar collectors, evaporators, condensers and relevant energy storage schemes during thermal charging and discharging. A brief overview of some energy storage options are also presented to motivate the inclusion of thermal energy storage into direct steam generation systems.
Highlights
During the past few decades, the demand for energy, related to electricity production and the production of thermal energy in industries around the world, has been steadily growing, and is projected to continue to do so
Kumar and Reddy (2018) compared two-phase flow correlations for thermo-hydraulic modelling of direct steam generation (DSG) in a solar parabolic trough collector (PTC) system. They assessed the validity of existing two-phase heat transfer and pressure drop correlations for a range of local temperature and pressure measurements obtained for DSG in a PTC test rig (DISS facility in Almeria, Spain) by Lobón et al (2014) The facility consists of 13 parabolictrough collectors connected in series, with a total length of 700 m where the collector tubes have an inner diameter of 25 mm
We considered direct steam generation systems as applied for concentrated solar power generation and process steam production
Summary
During the past few decades, the demand for energy, related to electricity production and the production of thermal energy in industries around the world, has been steadily growing, and is projected to continue to do so. In order for all of these processes to be adequately modelled and understood, a firm foundation in the thermohydraulic behaviour of the working fluid is required For this purpose, the paper is divided into the following sections: twophase flow regime maps, flow boiling, flow condensation, and energy storage options. At a particular operating condition, the prevailing two-phase flow regime has an impact on the heat transfer and pressure drop performance during boiling/evaporation and condensation in the various system components mentioned earlier. It indicates under which conditions the different flow regimes can be expected for that fluid. A drawback of such methods is that it requires the determination of probability function parameters for a large set of conditions since the approach is intrinsically not suitable to be used outside its proposed condition range (Canière, 2009)
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