A new GIS-based algorithm to estimate photovoltaic potential of solar train: Case study in Gyeongbu line, Korea
Photovoltaic (PV) power generation is considered a forward-looking industry. Nevertheless, solar energy is yet to become a direct source of electric power for mobile vehicles. Recently, there have been cases where solar panels were attached to the roof of trains to generate electricity. In this stud...
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| Published in | Renewable energy Vol. 190; pp. 713 - 729 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.05.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0960-1481 1879-0682 |
| DOI | 10.1016/j.renene.2022.03.130 |
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| Summary: | Photovoltaic (PV) power generation is considered a forward-looking industry. Nevertheless, solar energy is yet to become a direct source of electric power for mobile vehicles. Recently, there have been cases where solar panels were attached to the roof of trains to generate electricity. In this study, a method was devised to estimate the power generated by a solar train with panels. The solar irradiance on the roof of a moving train was calculated with respect to the location and time of the train, as well as the shadow effects of obstacles. The preprocessing of the input data required for calculating solar irradiation was executed through Geographic Information Systems, and finally, an algorithm for calculating solar irradiation and power generation was developed. With the algorithm-embodied Graphical User Interface, when spatial information of various routes is provided, the PV potential for each route can be calculated. Experimental calculations were conducted on the Gyeongbu line in Korea. During train operation, 122.15 MWh of power can be generated per year, with a reduction of 56 tons of CO2. The results of this preliminary evaluation are expected to accelerate the growth of the solar train industry. |
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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.2022.03.130 |