Short-term wind speed prediction model based on parallel integration of multiple networks

Bowei Yang; Shan Deng; Hui Qin; Guanjun Liu; Wanjiao Luo

doi:10.1117/12.3011603

7 December 2023 Short-term wind speed prediction model based on parallel integration of multiple networks

Bowei Yang, Shan Deng, Hui Qin, Guanjun Liu, Wanjiao Luo

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129414J (2023) https://doi.org/10.1117/12.3011603
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Wind speed prediction is of great importance for the control of wind power generation. For the problem of insufficient accuracy in wind speed prediction, this paper proposes a Multi-Network Parallel Integration Model (MNPIM), which is a combination of LSTM, GRU, RNN, ANN and a differential evolution algorithm to assign weights to the output of each sub-model in order to improve the accuracy of wind speed prediction. algorithm is used to assign weights to the output of each sub-model in order to improve the accuracy of wind speed prediction. The modelling and prediction of wind speed of a wind farm in Gansu Province is taken as an example, and the cross-validation method is introduced to partition the data set and compare with the existing LSTM, GRU, RNN, LR and GPR prediction methods.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bowei Yang, Shan Deng, Hui Qin, Guanjun Liu, and Wanjiao Luo "Short-term wind speed prediction model based on parallel integration of multiple networks", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129414J (7 December 2023); https://doi.org/10.1117/12.3011603

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available