Developing automated methods to estimate spectrally resolved direct normal irradiance for solar energy applications

Choi, Kelvin, Tsz Hei, Helen Brindley, N. Ekins-Daukes and Rodrigo Escobar

Renewable Energy, 2021, vol. 173, issue C, 1070-1086

Abstract: We describe four schemes designed to estimate spectrally resolved direct normal irradiance (DNI) for multi-junction concentrator photovoltaic systems applications. The schemes have increasing levels of complexity in terms of aerosol and circumsolar irradiance (CSI) treatment, ranging from a climatological aerosol classification with no account of CSI, to an approach which includes explicit aerosol typing and type dependent CSI contribution. When tested against ground-based broadband and spectral measurements at five sites spanning a range of aerosol conditions, the most sophisticated scheme yields an average bias of +0.068%, well within photometer calibration uncertainties. The average spread of error is 2.5%. These statistics are markedly better than the climatological approach, which carries an average bias of −1.76% and a spread of 4%. They also improve on an intermediate approach which uses Angström exponents to estimate the spectral variation in aerosol optical depth across the solar energy relevant wavelength domain. This approach results in systematic under and over-estimations of DNI at short and long wavelengths respectively. Incorporating spectral CSI particularly benefits sites which experience a significant amount of coarse aerosol. All approaches we describe use freely available reanalyses and software tools, and can be easily applied to alternative aerosol measurements, including those from satellite.

Keywords: Multi-jucnction solar cell; Concentrator photovoltaics; Aerosols; Circumsolar irradiance; Spectral direct normal irradiance; Solar energy resources (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:173:y:2021:i:c:p:1070-1086

DOI: 10.1016/j.renene.2021.03.127

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