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Modelling of solar photovoltaic module performance

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dc.contributor.author Mkasi, Hlaluku W
dc.contributor.author Lawrence, Pratt
dc.contributor.author Ayanna, Manjunath B
dc.contributor.author Roro, Kittessa T
dc.date.accessioned 2022-03-13T17:36:20Z
dc.date.available 2022-03-13T17:36:20Z
dc.date.issued 2021-11
dc.identifier.citation Mkasi, H.W., Lawrence, P., Ayanna, M.B. & Roro, K. 2021. Modelling of solar photovoltaic module performance. http://hdl.handle.net/10204/12322 . en_ZA
dc.identifier.isbn 978-0-7972-1878-9
dc.identifier.uri http://hdl.handle.net/10204/12322
dc.description.abstract The high demand for low carbon energy and rapidly decreasing solar panel prices have led to a surge in solar photovoltaic (PV) plants across the globe, more than at any other time since the industry began. Combined with geographic variations in environmental conditions, this has led to a vast increase in the need for characterisation of local spectral data. However, obtaining site-specific spectral data can be difficult for average users due to their high cost, varying accuracy, and difficulty to operate and maintain. Currently, users work with spectral data obtained from the American Society for Testing and Materials (ASTM) standard, satellites, and the Simple Model for Atmospheric Transmission of Sunshine (SMARTS) Model. To describe spectra generated by any of the above-mentioned sources, researchers have used average photon energy (APE) and other parameters. In this paper, we develop a method for describing PV site-specific clear sky 12-noon spectral data based on environmental conditions and spectral properties. The approach bins measured spectra into 100 and 200 nm wavelength ranges and characterises their changes throughout the year with the plane of array (PoA) irradiance, APE, air mass (AM) and sun elevation at the site to establish relationships. The method developed showed strong correlations between the APE and the PoA irradiance, the AM and the sun elevation in three clear sky days, each month over the period of three years. The observed strong correlations between these parameters indicate that when spectra cannot be measured, the measurable site’s environmental conditions can help determine the spectral content with strong confidence. en_US
dc.format Fulltext en_US
dc.language.iso es en_US
dc.source Southern African Sustainable Energy Conference, Lanzerac, Western Cape, 17-19 November 2021 en_US
dc.subject Air mass en_US
dc.subject Average photon energy en_US
dc.subject Binning en_US
dc.subject Plane of array irradiance en_US
dc.subject Sun elevation en_US
dc.subject Spectral distribution en_US
dc.subject Solar photovoltaic plants en_US
dc.title Modelling of solar photovoltaic module performance en_US
dc.type Conference Presentation en_US
dc.description.pages 7 en_US
dc.description.note Paper presented at Southern African Sustainable Energy Conference, Lanzerac, Western Cape, 17-19 November 2021 en_US
dc.description.cluster Smart Places en_US
dc.description.impactarea Energy Supply and Demand en_US
dc.identifier.apacitation Mkasi, H. W., Lawrence, P., Ayanna, M. B., & Roro, K. (2021). Modelling of solar photovoltaic module performance. http://hdl.handle.net/10204/12322 en_ZA
dc.identifier.chicagocitation Mkasi, Hlaluku W, Pratt Lawrence, Manjunath B Ayanna, and Kittessa Roro. "Modelling of solar photovoltaic module performance." <i>Southern African Sustainable Energy Conference, Lanzerac, Western Cape, 17-19 November 2021</i> (2021): http://hdl.handle.net/10204/12322 en_ZA
dc.identifier.vancouvercitation Mkasi HW, Lawrence P, Ayanna MB, Roro K, Modelling of solar photovoltaic module performance; 2021. http://hdl.handle.net/10204/12322 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Mkasi, Hlaluku W AU - Lawrence, Pratt AU - Ayanna, Manjunath B AU - Roro, Kittessa AB - The high demand for low carbon energy and rapidly decreasing solar panel prices have led to a surge in solar photovoltaic (PV) plants across the globe, more than at any other time since the industry began. Combined with geographic variations in environmental conditions, this has led to a vast increase in the need for characterisation of local spectral data. However, obtaining site-specific spectral data can be difficult for average users due to their high cost, varying accuracy, and difficulty to operate and maintain. Currently, users work with spectral data obtained from the American Society for Testing and Materials (ASTM) standard, satellites, and the Simple Model for Atmospheric Transmission of Sunshine (SMARTS) Model. To describe spectra generated by any of the above-mentioned sources, researchers have used average photon energy (APE) and other parameters. In this paper, we develop a method for describing PV site-specific clear sky 12-noon spectral data based on environmental conditions and spectral properties. The approach bins measured spectra into 100 and 200 nm wavelength ranges and characterises their changes throughout the year with the plane of array (PoA) irradiance, APE, air mass (AM) and sun elevation at the site to establish relationships. The method developed showed strong correlations between the APE and the PoA irradiance, the AM and the sun elevation in three clear sky days, each month over the period of three years. The observed strong correlations between these parameters indicate that when spectra cannot be measured, the measurable site’s environmental conditions can help determine the spectral content with strong confidence. DA - 2021-11 DB - ResearchSpace DP - CSIR J1 - Southern African Sustainable Energy Conference, Lanzerac, Western Cape, 17-19 November 2021 KW - Air mass KW - Average photon energy KW - Binning KW - Plane of array irradiance KW - Sun elevation KW - Spectral distribution KW - Solar photovoltaic plants LK - https://researchspace.csir.co.za PY - 2021 SM - 978-0-7972-1878-9 T1 - Modelling of solar photovoltaic module performance TI - Modelling of solar photovoltaic module performance UR - http://hdl.handle.net/10204/12322 ER - en_ZA
dc.identifier.worklist 25453 en_US


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