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Print ISSN: 1582-7445
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  2/2022 - 2

A New Wind Speed Evaluation Method Based on Pinball Loss and Winkler Score

LI, G., ZHANG, J. See more information about  ZHANG, J. on SCOPUS See more information about  ZHANG, J. on SCOPUS See more information about ZHANG, J. on Web of Science, SHEN, X. See more information about  SHEN, X. on SCOPUS See more information about  SHEN, X. on SCOPUS See more information about SHEN, X. on Web of Science, KONG, C. See more information about  KONG, C. on SCOPUS See more information about  KONG, C. on SCOPUS See more information about KONG, C. on Web of Science, ZHANG, Y. See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on Web of Science
 
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Download PDF pdficon (2,046 KB) | Citation | Downloads: 314 | Views: 172

Author keywords
wind speed forecasting, variational modal decomposition, neural network, Monte Carlo-Markov Chain stimulation, Winkler score

References keywords
wind(29), energy(24), speed(19), forecasting(19), term(12), short(12), prediction(11), power(9), model(9), applied(9)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2022-05-31
Volume 22, Issue 2, Year 2022, On page(s): 11 - 18
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2022.02002
Web of Science Accession Number: 000810486800002
SCOPUS ID: 85131767763

Abstract
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To reduce the adverse effects of the inherent stochastic volatility and uncontrollability of new energy on wind energy forecasting, this paper starting from the two aspects of improving the deterministic forecast and enhancing the predictability of volatility risk, the combination of variational modal decomposition (VMD), neural network and statistical model is applied to point forecasting, and the forecast model selection is based on the statistical characteristics of the components to enhance the degree of preciseness of wind speed forecasting. Then Monte Carlo-Markov Chain (MCMC) stimulation based on different quantiles is proposed to make interval prediction, and a new interval evaluation method is introduced, pinball loss function and Winkler score, to select the best interval prediction results for achieving precise control of wind power within a certain period of time. Finally, through experimental case verification, the performance of the advanced hybrid deterministic forecasting model is more advantageous than that of the traditional model. At the same time, the proposed interval prediction method better quantifies the uncertainty risk of wind power, makes up for the lack of a single evaluation method in the current interval prediction research, and can provide information support for the stable operation.


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References Weight

Web of Science® Citations for all references: 1,238 TCR
SCOPUS® Citations for all references: 1,476 TCR

Web of Science® Average Citations per reference: 33 ACR
SCOPUS® Average Citations per reference: 40 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2022-08-04 11:03 in 239 seconds.




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