posted on 2017-05-19, 09:14authored byKeith Gibson, Ian R. Cole, Brian Goss, Tom BettsTom 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
2017-04-21
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/.