The WRF-Solar Ensemble Prediction System to Provide Solar Irradiance Probabilistic Forecasts

被引：6

作者：

Kim, Ju-Hye ^{[2
]}

Munoz, Pedro Jimenez ^{[2
]}

Sengupta, Manajit ^{[1
]}

Yang, Jaemo ^{[1
]}

Dudhia, Jimy ^{[2
]}

Alessandrini, Stefano ^{[2
]}

Xie, Yu ^{[1
]}

机构：

[1] Natl Renewable Energy Lab, Golden, CO 80401 USA

[2] Natl Ctr Atmospher Res, Boulder, CO 80301 USA

来源：

IEEE JOURNAL OF PHOTOVOLTAICS | 2022年 / 12卷 / 01期

关键词：

Weather forecasting; Clouds; Forecasting; Calibration; Predictive models; Uncertainty; Probabilistic logic; Analog ensemble (AnEn); day-ahead forecast; ensemble forecast; National Solar Radiation Database (NSRDB); probabilistic forecast; stochastic perturbation; weather research and forecasting (WRF) solar; ANALOG ENSEMBLE; PART I; IMPLEMENTATION; MODEL;

D O I：

10.1109/JPHOTOV.2021.3117904

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

In this study, we introduce the recently developed WRF-solar ensemble prediction system and a calibration method. The performances of forecast models are evaluated using the National Solar Radiation Database observational analysis for day-ahead solar irradiance predictions. The results demonstrate that the ensemble forecast improves the quality of the forecasts by considering the uncertainty of each ensemble member. The analog ensemble calibration contributed to the reduction of positive bias and an overall improvement in the probabilistic attributes, such as reliability and statistical consistency.

引用

页码：141 / 144

页数：4

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