ULTRA SHORT-TERM WIND POWER PREDICTION BASED ON IMPROVED OSPERY OPTIMIZATION ALGORITHM AND VMD-LSTM

Luo Xiaoyuan; Liu Jie; Yang Bin; Qin Tao; Chen Changsheng; Yang Jing

doi:10.19912/j.0254-0096.tynxb.2023-1942

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (3) : 652-660. DOI: 10.19912/j.0254-0096.tynxb.2023-1942

ULTRA SHORT-TERM WIND POWER PREDICTION BASED ON IMPROVED OSPERY OPTIMIZATION ALGORITHM AND VMD-LSTM

Luo Xiaoyuan¹, Liu Jie², Yang Bin², Qin Tao¹, Chen Changsheng¹, Yang Jing^1,3

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Abstract

To enhance the accuracy of ultra-short-term wind power, a new optimization algorithm called improved osprey optimization algorithm （IOOA） is proposed. It combines Cauchy mutation and reverse learning strategy to optimize a combination prediction model based on long short-term memory network （LSTM） and variable mode decomposition （VMD）. Firstly, the historical wind power data collected through VMD is used to decompose the original power data with strong nonlinearity into relatively stable subsequences. Secondly, the osprey optimization algorithm, combining Cauchy mutation and reverse learning strategies, is used to optimize the number of hidden units, training period, and initial learning rate of the LSTM. Finally, the final prediction result is obtained by using a LSTM to predict each subsequence, and the predicted values of each subsequence were superimposed to obtain the final result.The proposed wind farm prediction model has been analyzed by using measured data. The results were compared with ordinary short-term memory neural network models. The proposed model reduced the RMSE by 62.5%, decreased MAPE by 62.2% and MAE by 55.9%. And the prediction accuracy is also higher than other four combination prediction models, indicating its success in improving the prediction accuracy of short-term wind power.

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long short-term memory network / variable mode decomposition / wind power / improved osprey optimization algorithm / power prediction / optimization algorithm

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Luo Xiaoyuan, Liu Jie, Yang Bin, Qin Tao, Chen Changsheng, Yang Jing. ULTRA SHORT-TERM WIND POWER PREDICTION BASED ON IMPROVED OSPERY OPTIMIZATION ALGORITHM AND VMD-LSTM[J]. Acta Energiae Solaris Sinica. 2025, 46(3): 652-660 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1942

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