Optimal geometry of solar cells with genetics algorithm
The introduction of flexible solar cells embedded in fabrics motivates the search for more efficient solar cell designs than flat panels. The optimal configuration of solar cells should receive the maximal flux density of sunlight rays over the course of a year. There may also be spatial restriction...
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| Main Authors | , |
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| Format | Conference Proceeding |
| Language | English |
| Published |
SPIE
27.02.2019
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| Online Access | Get full text |
| ISBN | 1510624686 9781510624689 |
| ISSN | 0277-786X |
| DOI | 10.1117/12.2510943 |
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| Summary: | The introduction of flexible solar cells embedded in fabrics motivates the search for more efficient solar cell designs than flat panels. The optimal configuration of solar cells should receive the maximal flux density of sunlight rays over the course of a year. There may also be spatial restrictions which only allow the cells to cover an arbitrary roof or area and surrounding structures which cast shadows in that area. So, it is difficult to analytically find the most efficient way to cover an arbitrary surface on Earth with solar cells. The genetic algorithm was used to find the optimal geometry for solar cells that have constant footprints at various latitudes. Random configurations of solar cells covering a constant area evolved into efficient configurations under the guidance of chosen selection, crossover, and mutation mechanisms. The results allow us to cover arbitrary roofs or areas as efficiently as possible, which greatly increases the value of solar energy. |
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| Bibliography: | Conference Date: 2019-02-02|2019-02-07 Conference Location: San Francisco, California, United States |
| ISBN: | 1510624686 9781510624689 |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2510943 |