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Design of CSP Plants with Optimally Operated Thermal Storage suboptimal for current CSP practice, it might assume practical significance in evaluating plants with different cost structure, e.g., featuring larger storage relative cost, as is case of PV/batteries installations. • The results have been obtained with open-source software, and a total of about 50 code lines. A future step of this research might involve the implementation of the proposed methodology as an extension of reference design models, such as the model implemented into the SAM program. 6.7 Acknowledgements This work has been carried out during E. Casati’s research period at Politecnico di Milano, Dipar- timento di Elettronica, Informazione e Bioingegneria, supported by the Dutch Technology Foun- dation STW, Applied Science Division of NWO and the Technology Program of the Ministry of Economic Affairs, grant # 11143. The authors thankfully acknowledge the precious suggestions about JModelica.org from their colleagues at the University of Lund, Sweden: F. Magnusson, J. Åkesson, and C. Andersson. The help received by the NREL staff working on the SAM support forum, in particular by P. Gilman, has also been invaluable. A.1 Solar Fields Design This section details the procedure adopted in order to obtain the design of the solar fields considered here. It shows how the field reflective surface ASF and its time-varying optical efficiency ηopt are defined, see Eq. 6.1. As described in §6.2, several solar fields characterized by different SM values are designed for the same hypothetical plant power output, location, and so forth, using the data reported in Tab. 2. For a given SM value, the adopted algorithm, based on the DELSOL3 code [30, 31], searches for a system design capable of yielding the highest financial returns, accounting for capital and other costs against the projected electricity production. The main objective of the tool is to optimize the geometric relationships among the main components of the solar power harvesting system, i.e., the solar field, the tower, and the receiver [25]. It is worth noting that all the designed fields share the design boundaries defined by the data in Tab. 2, aiming at reducing the complexity of the treatment and at facilitating the reproducibility of the results. The ranges of variation for the design variables, in particular, have been selected such that reasonable layouts can be obtained regardless of the considered SM value. The modelled receiver is of the tubular type, with constant absorptivity αREC and emissivity ǫcoating. The main constraint regarding the design of this component is the maximum admissible heat flux on its surface (see “rec. max flux”). Regarding the solar field, a general layout constraint is expressed in terms of the maximum/minimum distance of the farther/closer heliostats row from the tower (see “helio.-tow. distance/HTOW”). The modelled technology relies on square heliostats with a 12 m side (reflective part), whose main optical properties are also reported in Tab. 2. As anticipated in §6.5, these are arranged in a radially staggered, surround field which, for the sake of the layout optimization, is discretized in radial and azimuthal zones (see “N rad. zones” and “N azim. zones”). In order to solve the SF design problem, an optimal number of heliostats has to be allocated within each zone. The program evaluates discrete combinations of values for the main design variables, i.e. the diameter of the receiver DREC and its height-over-diameter ratio (H/D)REC, and the tower height HTOW, with a grid-spacing based on the search interval and on the number of 163PDF Image | New Concepts FOR Organic Rankine Cycle Power Systems
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