<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, a bias-correction of clear-sky models in prediction of the diffuse solar irradiance is presented. High quality ground date from two networks is used for model input and validation: aerosol optical depth from AERONET and diffuse solar irradiance from BSRN. Four established clear-sky models are tested: REST2, Yang, PS and MAC2. Two types of bias-corrections are developed: i) a correction for multiple aerosol scattering (MSC), accounting for extinction at high turbidity, and ii) a general regression on the model errors as a function of Sun elevation angle (h) and turbidity (β) correction (MOS). While the impact of MSC proves marginal, the MOS correction shows good results. Two versions of MOS are developed, one on the global dataset and a site-specific adaptation. Both versions bring significant improvements over the original implementation of the models, while the site-specific version reduces the errors with a few additional percentage points. The aggregate nRMSE of the REST2 model is reduced from 17.8% (no correction) to 11.3% (global MOS) and 9.4% (site-specific MOS).</p>
</abstract>

In this paper, a bias-correction of clear-sky models in prediction of the diffuse solar irradiance is presented. High quality ground date from two networks is used for model input and validation: aerosol optical depth from AERONET and diffuse solar irradiance from BSRN. Four established clear-sky models are tested: REST2, Yang, PS and MAC2. Two types of bias-corrections are developed: i) a correction for multiple aerosol scattering (MSC), accounting for extinction at high turbidity, and ii) a general regression on the model errors as a function of Sun elevation angle (h) and turbidity (β) correction (MOS). While the impact of MSC proves marginal, the MOS correction shows good results. Two versions of MOS are developed, one on the global dataset and a site-specific adaptation. Both versions bring significant improvements over the original implementation of the models, while the site-specific version reduces the errors with a few additional percentage points. The aggregate nRMSE of the REST2 model is reduced from 17.8% (no correction) to 11.3% (global MOS) and 9.4% (site-specific MOS).

Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Annals of West University of Timisoara - Physics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models"}

In this paper, a bias-correction of clear-sky models in prediction of the diffuse solar irradiance is presented. High quality ground date from two networks is...

Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Published Online: Nov 28, 2022

Page range: 95 - 107

Received: Aug 15, 2022

Accepted: Sep 09, 2022

DOI: https://doi.org/10.2478/awutp-2022-0007

Keywords
clear-sky models, diffuse solar irradiance, high turbidity, aerosol multiple scattering, model output statistics

© 2022 Robert Blaga, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Published Online: Nov 28, 2022

Page range: 95 - 107

Received: Aug 15, 2022

Accepted: Sep 09, 2022

DOI: https://doi.org/10.2478/awutp-2022-0007

Keywordsclear-sky models, diffuse solar irradiance, high turbidity, aerosol multiple scattering, model output statistics

© 2022 Robert Blaga, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
clear-sky models, diffuse solar irradiance, high turbidity, aerosol multiple scattering, model output statistics