Bias-Correction of Diffuse Solar Irradiance Modeled Through Parametric Models

Robert Blaga
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Abstract

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).
通过参数模型模拟的漫射太阳辐照度的偏差校正
摘要本文介绍了晴空模式在漫射太阳辐照度预报中的一种偏差校正方法。来自两个网络的高质量地面数据用于模型输入和验证:来自AERONET的气溶胶光学深度和来自BSRN的漫射太阳辐照度。测试了四种已建立的晴空模型:REST2、Yang、PS和MAC2。开发了两种类型的偏差校正:i)对多重气溶胶散射(MSC)的校正,考虑高浊度下的消光,ii)模型误差作为太阳高度角(h)和浊度(β)校正(MOS)的函数的一般回归。虽然MSC的影响被证明是微不足道的,但MOS校正显示出良好的效果。开发了两个版本的MOS,一个是基于全球数据集的,另一个是针对特定地点的。两个版本都对模型的原始实现进行了重大改进,而特定于站点的版本则通过几个额外的百分点减少了错误。REST2模型的总nRMSE从17.8%(未校正)降低到11.3%(全局MOS)和9.4%(特定站点MOS)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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