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

Ju Hye Kim; Pedro Jimenez Munoz; Manajit Sengupta; Jaemo Yang; Jimy Dudhia; Stefano Alessandrini; Yu Xie

doi:10.1109/JPHOTOV.2021.3117904

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

Ju Hye Kim
, Pedro Jimenez Munoz
, Manajit Sengupta
, Jaemo Yang
, Jimy Dudhia
, Stefano Alessandrini
, Yu Xie

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	141-144
Number of pages	4
Journal	IEEE Journal of Photovoltaics
Volume	12
Issue number	1
DOIs	https://doi.org/10.1109/JPHOTOV.2021.3117904
State	Published - Jan 1 2022

Keywords

Analog ensemble (AnEn)
National Solar Radiation Database (NSRDB)
day-Ahead forecast
ensemble forecast
probabilistic forecast
stochastic perturbation
weather research and forecasting (WRF) solar

Access to Document

10.1109/JPHOTOV.2021.3117904

Cite this

@article{9f2b843900354528b90c691efb9bbcad,

title = "The WRF-Solar Ensemble Prediction System to Provide Solar Irradiance Probabilistic Forecasts",

abstract = "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.",

keywords = "Analog ensemble (AnEn), National Solar Radiation Database (NSRDB), day-Ahead forecast, ensemble forecast, probabilistic forecast, stochastic perturbation, weather research and forecasting (WRF) solar",

author = "Kim, \{Ju Hye\} and \{Jimenez Munoz\}, Pedro and Manajit Sengupta and Jaemo Yang and Jimy Dudhia and Stefano Alessandrini and Yu Xie",

note = "Publisher Copyright: {\textcopyright} 2011-2012 IEEE.",

year = "2022",

month = jan,

day = "1",

doi = "10.1109/JPHOTOV.2021.3117904",

language = "English",

volume = "12",

pages = "141--144",

journal = "IEEE Journal of Photovoltaics",

issn = "2156-3381",

publisher = "IEEE Electron Devices Society",

number = "1",

}

TY - JOUR

T1 - The WRF-Solar Ensemble Prediction System to Provide Solar Irradiance Probabilistic Forecasts

AU - Kim, Ju Hye

AU - Jimenez Munoz, Pedro

AU - Sengupta, Manajit

AU - Yang, Jaemo

AU - Dudhia, Jimy

AU - Alessandrini, Stefano

AU - Xie, Yu

PY - 2022/1/1

Y1 - 2022/1/1

N2 - 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.

AB - 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.

KW - Analog ensemble (AnEn)

KW - National Solar Radiation Database (NSRDB)

KW - day-Ahead forecast

KW - ensemble forecast

KW - probabilistic forecast

KW - stochastic perturbation

KW - weather research and forecasting (WRF) solar

UR - https://www.scopus.com/pages/publications/85118272710

U2 - 10.1109/JPHOTOV.2021.3117904

DO - 10.1109/JPHOTOV.2021.3117904

M3 - Article

AN - SCOPUS:85118272710

SN - 2156-3381

VL - 12

SP - 141

EP - 144

JO - IEEE Journal of Photovoltaics

JF - IEEE Journal of Photovoltaics

IS - 1

ER -

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

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this