Verification of optical modelling of sunshape and surface slope error for concentrating solar power systems
| dc.contributor.author | Wang, Ye | |
| dc.contributor.author | Potter, Daniel | |
| dc.contributor.author | Asselineau, Charles-Alexis | |
| dc.contributor.author | Corsi, Clotilde | |
| dc.contributor.author | Wagner, Michael | |
| dc.contributor.author | Caliot, Cyril | |
| dc.contributor.author | Piaud, Benjamin | |
| dc.contributor.author | Blanco, Manuel | |
| dc.contributor.author | Kim, Jin-Soo | |
| dc.contributor.author | Pye, John | |
| dc.date.accessioned | 2024-02-05T21:28:21Z | |
| dc.date.available | 2024-02-05T21:28:21Z | |
| dc.date.issued | 2020 | |
| dc.date.updated | 2022-10-02T07:20:24Z | |
| dc.description.abstract | Sunshape and reflector surface slope error distributions are significant elements in modelling the optical behaviour of a concentrating solar power system. Different optical modelling tools implement these elements with various approaches. Discrepancies can easily accumulate in simulations of a large optical system as a result of incorrect implementations. This study reviews and verifies the implementations of these two factors in six tools that are widely used for optical modelling in solar energy research: Tonatiuh, SolTrace, Tracer, Solstice, Heliosim and SolarPILOT. The review incorporates three rounds of tests. Firstly, basic tests examine each factor carefully in simplified on-axis reflector–target configurations (round ‘A’). Secondly, off-axis effects are introduced (round ‘B’). Thirdly, full heliostat field simulations are verified (round ‘C’). All of the test cases are simulated with each modelling tool, and results are compared. Discrepancies were observed due to approximations inherent in the cone optics (convolution) methods, incorrect implementation the of pillbox slope errors, different approaches to setting the circumsolar ratio for the Buie sunshape, and different approaches to the calculation of blocking and shading losses in some tools. All issues are discussed fully, and solutions to most issues were implemented within the scope of the present study. Some remaining issues are noted. The study highlights the importance of careful implementation of these aspects of optical modelling and contributes to an improvement in the quality of several widely-used tools. | en_AU |
| dc.description.sponsorship | This work is a collaboration between the Australian National University (ANU), CSIRO, NREL, PROMES-CNRS, Méso-Star Company and the Cyprus Institute. The authors gratefully acknowledge the support of (1) the European Union's Horizon 2020 Research and Innovation Programme, within the context of the Cyprus Institute’s CySTEM ERA Chair project, under Grant Agreement No. 667942, (2) the French ‘‘Investments for the future” program managed by the National Agency for Research (ANR) No. ANR-10-LABX-22-01-SOLSTICE and (3) the Australian Renewable Energy Agency, 2014/RND010. | en_AU |
| dc.format.mimetype | application/pdf | en_AU |
| dc.identifier.issn | 0038-092X | en_AU |
| dc.identifier.uri | http://hdl.handle.net/1885/313217 | |
| dc.language.iso | en_AU | en_AU |
| dc.provenance | This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). | en_AU |
| dc.publisher | Pergamon-Elsevier Ltd | en_AU |
| dc.rights | © 2019 The authors | en_AU |
| dc.rights.license | Creative Commons Attribution licence | en_AU |
| dc.rights.uri | http://creativecommons.org/licenses/ by-nc-nd/4.0/ | en_AU |
| dc.source | Solar Energy | en_AU |
| dc.subject | Optical modelling | en_AU |
| dc.subject | Verification | en_AU |
| dc.subject | Sunshape | en_AU |
| dc.subject | Surface slope error | en_AU |
| dc.subject | Monte Carlo ray tracing | en_AU |
| dc.subject | Cone optics | en_AU |
| dc.title | Verification of optical modelling of sunshape and surface slope error for concentrating solar power systems | en_AU |
| dc.type | Journal article | en_AU |
| dcterms.accessRights | Open Access | en_AU |
| local.bibliographicCitation.issue | 1 | en_AU |
| local.bibliographicCitation.lastpage | 474 | en_AU |
| local.bibliographicCitation.startpage | 461 | en_AU |
| local.contributor.affiliation | Wang, Ye, College of Engineering and Computer Science, ANU | en_AU |
| local.contributor.affiliation | Potter, Daniel, CSIRO Energy | en_AU |
| local.contributor.affiliation | Asselineau, Charles-Alexis, College of Engineering and Computer Science, ANU | en_AU |
| local.contributor.affiliation | Corsi, Clotilde, CSIRO Energy | en_AU |
| local.contributor.affiliation | Wagner, Michael, National Renewable Energy Laboratory | en_AU |
| local.contributor.affiliation | Caliot, Cyril, CNRS | en_AU |
| local.contributor.affiliation | Piaud, Benjamin, Méso-Star | en_AU |
| local.contributor.affiliation | Blanco, Manuel, The Cyprus Institute | en_AU |
| local.contributor.affiliation | Kim, Jin-Soo, CSIRO Energy Technology | en_AU |
| local.contributor.affiliation | Pye, John, College of Engineering and Computer Science, ANU | en_AU |
| local.contributor.authoruid | Wang, Ye, u5712676 | en_AU |
| local.contributor.authoruid | Asselineau, Charles-Alexis, u5279029 | en_AU |
| local.contributor.authoruid | Pye, John, u3627027 | en_AU |
| local.description.notes | Imported from ARIES | en_AU |
| local.identifier.absfor | 401700 - Mechanical engineering | en_AU |
| local.identifier.ariespublication | u6269649xPUB874 | en_AU |
| local.identifier.citationvolume | 195 | en_AU |
| local.identifier.doi | 10.1016/j.solener.2019.11.035 | en_AU |
| local.identifier.scopusID | 2-s2.0-85075731535 | |
| local.identifier.thomsonID | WOS:000509632000043 | |
| local.publisher.url | https://www.sciencedirect.com/ | en_AU |
| local.type.status | Published Version | en_AU |
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