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Compensation of temporal averaging bias in solar irradiance data

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journal contribution
posted on 19.05.2017 by Keith Gibson, Ian R. Cole, Brian Goss, Tom Betts, Ralph Gottschalg
Solar irradiance data is used for the prediction of solar energy system performance but is presently a significant source of uncertainty in energy yield estimation. This also directly affects the expected revenue, so the irradiance uncertainty contributes to project risk and therefore the cost of finance. In this paper, the combined impact of temporal averaging, component deconstruction and plane translation mechanisms on uncertainty is analysed. A new method to redistribute (industry standard) hourly averaged data is proposed. This clearness index redistribution method is based on the statistical redistribution of clearness index values and largely corrects the bias error introduced by temporal averaging. Parameters for the redistribution model were derived using irradiance data measured at high temporal resolution by CREST, Loughborough University, over a 5 year period. The root mean square error (RMSE) of example net annual (2014) diffuse, beam and global yield of hourly averaged data were reduced from approximately 15% to 1%, 14% to 3% and 4% to 1%, respectively.

Funding

This work has been conducted as part of the research project ‘PV2025 - Potential Costs and Benefits of Photovoltaic for UK Infrastructure and Society’ project which is funded by the RCUK's Energy Programme (contract no: EP/K02227X/1).

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IET Renewable Power Generation

Volume

11

Issue

10

Citation

GIBSON, K. ... et al, 2017. Compensation of temporal averaging bias in solar irradiance data. IET Renewable Power Generation, 11 (10), pp. 1288-1294.

Publisher

Institution of Engineering and Technology (IET)

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Acceptance date

21/04/2017

Publication date

2017-05-02

Notes

This is an Open Access Article. It is published by IET under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/.

ISSN

1752-1416

eISSN

1752-1424

Language

en

Licence

Exports