WIND FARM POWER PREDICTION BASED ON IMPROVED OSPREY OPTIMIZATION ALGORITHM

Zhu Binglei; Wang Anran; Zhao Zhengyang; Luo Ting; Wang Jiangjie; Zhang Kai

doi:10.19912/j.0254-0096.tynxb.2025-0383

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (7) : 163-173. DOI: 10.19912/j.0254-0096.tynxb.2025-0383

WIND FARM POWER PREDICTION BASED ON IMPROVED OSPREY OPTIMIZATION ALGORITHM

Zhu Binglei¹, Wang Anran², Zhao Zhengyang¹, Luo Ting¹, Wang Jiangjie¹, Zhang Kai¹

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Abstract

To improve the accuracy and stability of wind farm power forecasting, a wind farm prediction model based on a long short-term memory neural network （LSTM） optimized by an improved osprey optimization algorithm （IOOA） is proposed. A combination of bidirectional long short-term memory network （BiLSTM） and convolutional neural network （CNN） is used to leverage the advantages of both models to capture the complex nonlinear spatiotemporal relationships presented by wind farm power data, mine the hidden patterns and features, and introduce an attention mechanism to adjust the weight of the captured information. To address the issues of slow convergence and susceptibility to local optima in the osprey optimization algorithm （OOA）, a method using the Levy flight strategy and Logistic chaotic mapping is proposed to enhance the OOA's search capability, after which the improved osprey optimization algorithm （IOOA） is used to optimize the model parameters. The results show that, compared to the better-performing CNN-BiLSTM-Attention prediction model, the proposed IOOA-CNN-BiLSTM-Attention model reduces the root mean square error （RMSE）, mean absolute error （MAE）, and mean absolute percentage error （MAPE） by 55.287%, 54.352%, and 32.283%, respectively, while R² improves to 96.635%, demonstrating better stability and forecasting accuracy.

Key words

wind power / forecasting / convolutional neural networks / attention mechanism / bidirectional long short-term memory network / osprey optimization algorithm

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Zhu Binglei, Wang Anran, Zhao Zhengyang, Luo Ting, Wang Jiangjie, Zhang Kai. WIND FARM POWER PREDICTION BASED ON IMPROVED OSPREY OPTIMIZATION ALGORITHM[J]. Acta Energiae Solaris Sinica. 2026, 47(7): 163-173 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0383

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