There are many concerns regarding the design and deployment of a heliostat field (Imenes et al., 2006), the aiming strategy for the heliostats (Wang et al., 2017), and the estimation of the yearly received energy (Islam et al., 2018). The concentrated radiation energy heats the transfer fluid in the central receiver, such as water or molten salt, for subsequent electricity generation (Conroy et al., 2018). The heliostats track the movement of the sun and concentrate the lights they reflect onto the surface of a central receiver, which is usually mounted on top of a tower (Behar et al., 2013). In this type of CRS, thousands of highly reflective mirrors, known as heliostats, are deployed to form a heliostat field. The most common central receiver systems (CRSs) (Behar et al., 2013, Li et al., 2016, Levêque et al., 2017) are power facilities for converting solar energy into electrical energy (Lovegrove and Stein, 2012, Duffie et al., 2013).
Soltrace free version software#
QMCRT also has an advantage in terms of efficiency for CRS compared with two well-known simulation software tools, i.e., SolTrace and Tonatiuh.Įfforts regarding the development and utilization of solar energy are attracting increasing attention because of its clean and renewable nature. Compared with the state-of-the-art GPU-based grid ray tracing (GRT) approach, QMCRT is equally fast but generates a more accurate result. QMCRT is two orders of magnitude faster than the traditional MCRT method when addressing traditional one-reflection CRS case. The results obtained for both synthetic and real heliostats obtained using QMCRT are substantially in keeping with the results obtained using established computational tools. As a result, a stable MaxRF value approaching the reference value is obtained, while the total power remains almost unchanged. In QMCRT, the problem is solved by applying a trimmed mean smoothing operation to the generated radiative flux distribution. Second, in the traditional approaches, the simulated maximum radiative flux (MaxRF) is randomly higher than the reference value, even if tens of millions of rays are traced. This method also facilitates sunshape sampling and heliostat surface slope error sampling, which can achieve memory and run-time efficiency. First, QMCRT, as a bidirectional approach, can avoid unnecessary intersection calculations. In this paper, a GPU-based ray-tracing simulation method, namely, quasi-Monte Carlo ray tracing (QMCRT), is proposed to address problems of both efficiency and accuracy. MCRT is an effective method to describe the radiative flux distribution on the receiver surface reflected by either a single heliostat or all heliostats in a heliostat field. The collectors have also been mathematically modeled, and the numerical data have been validated against the experimental measurements.Monte Carlo ray tracing (MCRT) is a fundamental simulation method for central receiver systems(CRSs). The performance of the described collectors has been experimentally characterized at the Solar Energy Conversion Laboratory of the University of Padova (45.4°N, 11.9☎), Italy. The other receiver has been designed for cogeneration of electricity and heat (CPVT), and it is equipped with triple-junction photovoltaic cells, which are actively cooled by an aluminum roll-bond heat exchanger. One receiver has been designed for thermal energy extraction, and it consists of a canalized roll-bond plate provided with a semi-selective coating. In this system, two types of flat receivers have been tested.
The second system is a parabolic trough concentrator (PTC) with two-axis solar tracking: the primary optics consists of a segment of parabolic cylinder which concentrates the direct normal irradiance (DNI) on a linear receiver. Each evacuated tube is composed of an outer glass envelope and a glass absorber with selective coating in thermal contact, via absorber fin, with a U-shaped channel for the liquid flow.
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The first solar device is a stationary compound parabolic concentrator (CPC) collector: it is provided with truncated or full CPC reflectors and evacuated tubes. Two solar thermal systems with different designs and, accordingly, different concentration ratios have been studied. This chapter describes the performance analysis of different concentrating technologies through experimental and numerical modeling activities.
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