Short-term Wind Power Prediction Based on Improved Dung Beetle Optimization Algorithm
[1]JIANG Jiandong,ZHANG Haifeng,GUO Jiaqi.Short-term Wind Power Prediction Based on Improved Dung Beetle Optimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2025,46(04):129-136.[doi:10.13705/j.issn.1671-6833.2025.01.015]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
46
Number of periods:
2025 04
Page number:
129-136
Column:
Public date:
2025-07-10
- Title:
- Short-term Wind Power Prediction Based on Improved Dung Beetle Optimization Algorithm
- CLC:
- TM614
- Abstract:
- A short-term wind power prediction model based on POTDBO-VMD-CNN-BiLSTM was proposed to improve the accuracy of short-term wind power prediction. Firstly, three strategies were adopted to improve the dung beetle optimization algorithm, including integrating Piecewise chaotic mapping, integrating Osprey optimization algorithm, and integrating adaptive T-distribution perturbation, in order to balance the global exploration and local development capabilities of the dung beetle optimization algorithm and accelerate its convergence speed. Secondly, the improved dung beetle optimization algorithm ( POTDBO) was used to optimize the decomposition number and penalty factor of variational mode decomposition (VMD) to improve the decomposition effect of VMD. Then, the POTDBO-VMD model was used to decompose the wind power. Finally, the decomposed frequency components and residual components were input into the CNN-BiLSTM hybrid model for prediction, and the prediction results of each frequency component and residual component were sequentially reconstructed to obtain the wind power prediction results. The proposed model was experimentally tested using actual data from wind farms in Xinjiang and Jilin. Compared with the CNN-BiLSTM model, the results showed that the proposed model increased by 4. 21% and 7. 69% on R 2 respectively, demonstrating better prediction accuracy.
- References:
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Last Update:
2025-07-13