Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching

Wenting Wang; Yufeng Guo; Dazhi Yang; Jan Kleissl

doi:10.1109/SPIES55999.2022.10082270

Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching

Wenting Wang^*
, Yufeng Guo
, Dazhi Yang^*
, Jan Kleissl

^*Corresponding author for this work

School of Electrical Engineering and Automation, Harbin Institute of Technology
University of California at San Diego

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Accurate solar power forecasting has a decisive effect on the formulation of day-ahead power system dispatch strategies. At present, there is every confidence that paring numerical weather prediction with a physical model chain is the state-of-the-art solar forecasting method suitable for grid integration. Leveraging this two-stage solar power forecasting framework, the total cost benefits of day-ahead power system dispatch have been quantified based on a modified IEEE 24-bus system. The numerical experiment results reveal that the two-stage forecasting method saves 2.1 million dollars (1.33%) per year, as compared to the benchmark.

Original language	English
Title of host publication	2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2081-2086
Number of pages	6
ISBN (Electronic)	9781665489577
DOIs	https://doi.org/10.1109/SPIES55999.2022.10082270
State	Published - 2022
Externally published	Yes
Event	4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022 - Beijing, China Duration: 9 Dec 2022 → 12 Dec 2022

Publication series

Name	2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022

Conference

Conference	4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022
Country/Territory	China
City	Beijing
Period	9/12/22 → 12/12/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

day-ahead dispatching
numerical weather prediction
physical model chain
solar power forecasting

Access to Document

10.1109/SPIES55999.2022.10082270

Cite this

Wang, W., Guo, Y., Yang, D., & Kleissl, J. (2022). Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching. In 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022 (pp. 2081-2086). (2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPIES55999.2022.10082270

Wang, Wenting ; Guo, Yufeng ; Yang, Dazhi et al. / Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching. 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 2081-2086 (2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022).

@inproceedings{6f03233adc664f3e8519462db5220c51,

title = "Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching",

abstract = "Accurate solar power forecasting has a decisive effect on the formulation of day-ahead power system dispatch strategies. At present, there is every confidence that paring numerical weather prediction with a physical model chain is the state-of-the-art solar forecasting method suitable for grid integration. Leveraging this two-stage solar power forecasting framework, the total cost benefits of day-ahead power system dispatch have been quantified based on a modified IEEE 24-bus system. The numerical experiment results reveal that the two-stage forecasting method saves 2.1 million dollars (1.33\%) per year, as compared to the benchmark.",

keywords = "day-ahead dispatching, numerical weather prediction, physical model chain, solar power forecasting",

author = "Wenting Wang and Yufeng Guo and Dazhi Yang and Jan Kleissl",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022 ; Conference date: 09-12-2022 Through 12-12-2022",

year = "2022",

doi = "10.1109/SPIES55999.2022.10082270",

language = "英语",

series = "2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2081--2086",

booktitle = "2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022",

address = "美国",

}

Wang, W, Guo, Y , Yang, D & Kleissl, J 2022, Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching. in 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022. 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022, Institute of Electrical and Electronics Engineers Inc., pp. 2081-2086, 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022, Beijing, China, 9/12/22. https://doi.org/10.1109/SPIES55999.2022.10082270

Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching. / Wang, Wenting; Guo, Yufeng ; Yang, Dazhi et al.
2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 2081-2086 (2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching

AU - Wang, Wenting

AU - Guo, Yufeng

AU - Yang, Dazhi

AU - Kleissl, Jan

PY - 2022

Y1 - 2022

N2 - Accurate solar power forecasting has a decisive effect on the formulation of day-ahead power system dispatch strategies. At present, there is every confidence that paring numerical weather prediction with a physical model chain is the state-of-the-art solar forecasting method suitable for grid integration. Leveraging this two-stage solar power forecasting framework, the total cost benefits of day-ahead power system dispatch have been quantified based on a modified IEEE 24-bus system. The numerical experiment results reveal that the two-stage forecasting method saves 2.1 million dollars (1.33%) per year, as compared to the benchmark.

AB - Accurate solar power forecasting has a decisive effect on the formulation of day-ahead power system dispatch strategies. At present, there is every confidence that paring numerical weather prediction with a physical model chain is the state-of-the-art solar forecasting method suitable for grid integration. Leveraging this two-stage solar power forecasting framework, the total cost benefits of day-ahead power system dispatch have been quantified based on a modified IEEE 24-bus system. The numerical experiment results reveal that the two-stage forecasting method saves 2.1 million dollars (1.33%) per year, as compared to the benchmark.

KW - day-ahead dispatching

KW - numerical weather prediction

KW - physical model chain

KW - solar power forecasting

UR - https://www.scopus.com/pages/publications/85153386318

U2 - 10.1109/SPIES55999.2022.10082270

DO - 10.1109/SPIES55999.2022.10082270

M3 - 会议稿件

AN - SCOPUS:85153386318

T3 - 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022

SP - 2081

EP - 2086

BT - 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022

Y2 - 9 December 2022 through 12 December 2022

ER -

Wang W, Guo Y , Yang D, Kleissl J. Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching. In 2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 2081-2086. (2022 4th International Conference on Smart Power and Internet Energy Systems, SPIES 2022). doi: 10.1109/SPIES55999.2022.10082270

Solar Power Forecasting Based on Numerical Weather Prediction and Physical Model Chain for Day-ahead Power System Dispatching

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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