Comparison of Heliostat Field Layout Design Methodologies and Impact on Power Plant Efficiency

Abstract

The aim of this paper is the presentation of a study of heliostat field layout performances for a CSP plant, based on the central receiver technology, using different algorithms for layout generation. The purpose is to perform a detailed comparison of the layout performances in terms of efficiency and energy yield to determine the algorithms benefits and drawbacks at various scenarios as first step on the optimization of the heliostat layouts designs. The layouts compared are generated using a genetic optimization process and using different objective functions for each studied case. Results show that new biomimetic algorithms are a good alternative to classical algorithm patterns based on the radial staggered method. However, these results are only valid for the analyzed cases.

Optimizing the Heliostat Field Layout by Applying Stochastic Population-Based Algorithms

“…This distribution pattern is also characterized by achieving a good trade-off between land use and field efficiency. For instance, in Mutuberria et al (2015), its good properties are also observed. The method is inspired by the spiral patterns of the phyllotaxis disc, like florets on the head of sunflowers.…”

“…10), and the biomimetic spiral, recently proposed by Noone et al (2012), are two examples of patterns. In Mutuberria et al (2015), where several patterns are compared, more examples and references can be found. The second strategy is to select final heliostat positions from a defined set (as iteratively done in Sánchez and Romero, 2006).…”

Design of a parallel genetic algorithm for continuous and pattern-free heliostat field optimization

“…In [18], it is proposed an innovative bio-inspired pattern based on a Fermat spiral. That layout has become really popular: it has been used, for instance, in [3], and successfully compared to other patterns [17,32]. To attenuate their rigidity, patterns are often applied to generate oversize fields before finally selecting the minimum required heliostats [3,18,20].…”

“…However, its simple and parallel structure aims to be a valuable component of a complete field design methodology. Although genetic algorithms have already been used for heliostat field optimization, the focus is usually on reduced sets of parameters as in [3,17,19,20]. Similarly, the use of high-performance computing is not a new proposal of this work.…”

Hector, a new methodology for continuous and pattern-free heliostat field optimization

“…A classic and popular one is radial staggering [17], which inspires some recent proposals [13,9,18]. An example of modern pattern is the spiral proposed in [7], which has attracted the interest of several researchers [19,20,21]. Regarding the iterative deployment of heliostats, the work in [10] is one of the most popular ones.…”