A model-based approach for optical performance assessment and optimization of a solar dish
The solar dish is a point-focusing concentrator with a very high concentration ratio ranging from hundreds to thousands. Practical assessment and optimization methods are necessary to assemble solar dishes with satisfying concentration ratios and flux density distributions, which is very important f...
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| Published in: | Renewable energy Vol. 100; pp. 103 - 113 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.01.2017
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| Subjects: | |
| ISSN: | 0960-1481, 1879-0682 |
| Online Access: | Get full text |
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| Summary: | The solar dish is a point-focusing concentrator with a very high concentration ratio ranging from hundreds to thousands. Practical assessment and optimization methods are necessary to assemble solar dishes with satisfying concentration ratios and flux density distributions, which is very important for the overall solar thermal systems to achieve high efficiency. A solar dish usually consists of many mirror facets installed on a supporting structure with a dual-axis tracking system. Small mirror facets are easy to manufacture, but the alignment of many mirror facets is very challenging. A model-based approach for optical performance assessment and optimization of a solar dish was proposed, and flux density measurements were carried out to validate the approach. The simulation and experimental results showed very good consistency and suggested that the concentration ratio and the intercept factor could be increased from ∼500 to ∼1500 and 0.66 to 0.9 respectively after assembly optimization.
•Photogrammetry combined with 3D laser scanning was used to measure dish surface.•Unified error model was used to capture major manufacturing and assembling errors.•Flux density measurements under moon light validated model simulation results.•Dish optimization improve concentration ratio by 3× and intercept factor by ∼40%. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0960-1481 1879-0682 |
| DOI: | 10.1016/j.renene.2016.05.076 |