Dhimish, Mahmoud, Mather, Peter, Holmes, Violeta et al. (1 more author) (2019) CDF modelling for the optimum tilt and azimuth angle for PV installations:case study based on 26 different locations in region of the Yorkshire UK. IET Renewable Power Generation. pp. 399-408. ISSN 1752-1424
Abstract
The optimum tilt and azimuth angle for PV installations in 26 different locations within the county of Yorkshire, UK have been evaluated. In order to examine the performance of the PV systems, a selection of criteria has been identified as follows: (i) the maximum difference in the age of the PV installations is no older than two years, (ii) PV modules technology is crystalline-Silicon (c-Si), (iii) maximum area of study in each location is 20 km 2 , and (iv) PV systems have either the same tilt or azimuth angle within ±2°. The Huddersfield area was used as the primary example to evaluate the proposed methodology. The optimum tilt and azimuth angle for PV installations in the area is 39° and -1° respectively. Moreover, based on 4 kWp PV installations observed in all studied locations, a geographical map representing the annual energy production in the 26 locations has been drawn. The maximum annual energy production is observed for the city of Hull, whereas the minimum observed for the town of Keighley. Finally, the evaluation of the overall annual energy production is discussed using the analysis of the direct normal irradiance (DNI), ambient temperature, air frost, and the cloudiness.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 IET. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 02 Sep 2021 14:10 |
Last Modified: | 08 Feb 2025 00:43 |
Published Version: | https://doi.org/10.1049/iet-rpg.2018.5301 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1049/iet-rpg.2018.5301 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177719 |