Heliostat Cost Optimization Study

Heliostat Cost Optimization Study Finn von Reeken1, Gerhard Weinrebe2, Thomas Keck2, Otmar Dreyer2, Markus Balz2 1

Dipl.-Ing (FH), Engineer, schlaich bergermann und partner, sbp sonne gmbh,

Schwabstraße 43, 70197 Stuttgart, Germany; +49 711 648710, [email protected] 2

schlaich bergermann und partner, sbp sonne gmbh, Schwabstraße 43, 70197 Stuttgart, Germany.

1. Introduction Typically, heliostat fields contribute about 50 % to power tower overall investment costs. Therefore heliostat field optimization and cost reduction is of paramount importance to make power towers economically viable. The work described in this paper targets at the identification of the most cost efficient heliostat design and size. This task is very extensive, if a consistent result shall be obtained, because heliostats of different sizes do also require different structures; just scaling the same design will not yield a meaningful result. Such a procedure may result in heliostats of different sizes and different specific cost, but they will not be optimum heliostats. Furthermore, total costs are worked out for every size and the respective design, since the effort for assembly, erection and maintenance depends on size and the corresponding number of heliostats required for a given design power. Therefore the results presented are not ‘the optimum heliostat size in general’, but the most cost effective variant (combination of size and structural/mechanical design) of all variants investigated here. As the optical quality of the individual variants is not identical, specific costs of the heliostats (measured e.g. in Euros per square meter of concentrator surface) are not an appropriate figure of merit [1] [2]. Instead, field performance must be considered, too. To this end optical quality and tracking accuracy have to be factored in. This is accomplished by simulating heliostat fields and the corresponding receiver/power block subsystem and evaluating the resulting levelised costs of electricity (LCOE). LCOE found must not be considered as absolute values that can be used for a crucial financial project evaluation; uncertainties concerning some cost factors (e.g. the cost of mirrors per square meter) are still too high for such a task. Nevertheless, as these uncertainties apply to all heliostat variants investigated in about the same way, ranking of the heliostats is not affected. Thus the method employed can be considered well suited to identify the most cost effective combination of heliostat size and design.

2. Summary of the Study The goal of this study is to identify cost effective heliostat designs for a 65 MW power tower to be installed at Upington, South Africa. To this end, the following methodology has been used: First different variants of small, medium sized and large heliostats are designed. Then the respective costs, tracking and optical quality are determined. For the calculation of optical quality a structural model of the heliostat is programmed and analyzed using finite element software. By doing so, deviations of the reflector normals from their desired design orientation due to dead load and wind are calculated. Then the heliostat designs are varied with regard to: 

Structural stiffness. Sections and structural concept are varied and hence optical quality. The effect on costs mainly due to differences in steel mass and the assembly and installation effort required and optical quality is calculated.

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Concentrator optical quality. This is accomplished by varying the number of mirror facet support points. Again the resulting effect on costs and optical quality is determined.

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Tracking quality. Different drive concepts are analyzed regarding their respective costs and the achievable tracking accuracy.

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Tracking axes arrangement. Conventional azimuth-elevation heliostats as well as heliostats with a novel axes arrangement named 'slope drive' have been designed and analyzed. The 'slope drive' setup results in comparatively small angular ranges required for tracking, but it also calls for a different structural concept of the reflector and requires higher pedestals.

Eventually SAM is used to calculate levelised electricity costs for a reference power tower plant equipped with heliostat fields composed of each of the analyzed heliostats. Before each annual simulation run the heliostat field is optimized using SAM built-in PTGen field optimization tool. Weather data for Upington is used, financial parameters and power block efficiency were agreed with the South African client SASOL, before it pulled out of the CSP race. For all other values the SAM defaults are used. Calculated LCOEs are then used to identify the most suitable option(s). Results: Calculated LCOE vary by ±15 %. Medium sized heliostats (~40 m²) with a slope drive result in lowest LCOEs (15.0 ¢/kWh).

Fig. 1: Selection of analyzed heliostat basic variants

Fig. 1: Schematic procedure References [1] G. Weinrebe, F. von Reeken, M. Wöhrbach, T. Plaz, V. Göcke, and M. Balz, “Towards Holistic Power Tower System Optimization,” presented at the SolarPACES2013, Las Vegas, NV, USA, 2013. [2] T. Keck, M. Balz, H. Haberstroh, C. Husenbeth, G. Weinrebe, and B. Zwingmann, “Techno-economical evaluation of power tower system layout with specific view on heliostat design optimization and tower costs,” presented at the SolarPACES 2012, Marrakesh, 2012.