Numerical weather prediction (NWP) is widely used for day-ahead solar irradiance forecast, which is essential for applications in day-ahead energy market and energy management of different scales ranging from public level to civil level. In the literature, many NWP correction methods have been proposed to obtain more accurate solar irradiance forecast. However, when facing different real-world scenarios, it is crucial to efficiently design corresponding correction schemes, which require a detailed and reliable error evaluation foundation. To solve this problem, the performance for day-ahead NWP Global Horizontal Irradiance (GHI) forecast is evaluated under different weather conditions and seasons. The statistical analysis was conducted at each time of day and each NWP GHI forecast level with both publicly available datasets and actual field dataset, aiming to explore the detailed error characteristics of NWP GHI forecasts. The results demonstrate variations in NWP GHI error across diverse weather conditions and seasons, which indicates that future NWP GHI corrections should be developed under different weather conditions and seasons. For weather conditions, NWP GHI forecasts have the lowest accuracy during overcast conditions, followed by cloudy conditions, while the highest accuracy is observed during sunny conditions. Moreover, overestimations are more likely to occur during overcast and cloudy conditions. For seasons, the accuracy of NWP GHI forecasts is generally highest during winter. Additionally, we have summarized some common error characteristics under different weather conditions and seasons. This study provides useful information for improving the accuracy and efficiency of NWP correction works and for the stable operation of power systems.
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July 2024
Research Article|
August 23 2024
Evaluation of performance for day-ahead solar irradiance forecast using numerical weather prediction
Weijing Dou
;
Weijing Dou
(Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
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Kai Wang
;
Kai Wang
(Formal analysis, Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
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Shuo Shan
;
Shuo Shan
(Methodology, Supervision, Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
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Chenxi Li;
Chenxi Li
(Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
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Jiahao Wen;
Jiahao Wen
(Formal analysis, Software)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
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Kanjian Zhang
;
Kanjian Zhang
(Funding acquisition, Project administration, Supervision, Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
2
Southeast University Shenzhen Research Institute
, Shenzhen 518063, China
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Haikun Wei
;
Haikun Wei
a)
(Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing)
1
Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University
, Nanjing 210096, China
2
Southeast University Shenzhen Research Institute
, Shenzhen 518063, China
a)Author to whom correspondence should be addressed: hkwei@seu.edu.cn
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Victor Sreeram
Victor Sreeram
(Supervision, Writing – review & editing)
3
Department of Electrical, Electronics and Computer Engineering, The University of Western Australia
, Perth, Australia
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a)Author to whom correspondence should be addressed: hkwei@seu.edu.cn
J. Renewable Sustainable Energy 16, 043703 (2024)
Article history
Received:
April 29 2024
Accepted:
August 05 2024
Citation
Weijing Dou, Kai Wang, Shuo Shan, Chenxi Li, Jiahao Wen, Kanjian Zhang, Haikun Wei, Victor Sreeram; Evaluation of performance for day-ahead solar irradiance forecast using numerical weather prediction. J. Renewable Sustainable Energy 1 July 2024; 16 (4): 043703. https://doi.org/10.1063/5.0216528
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