Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM

Wang，Zhen1; Ying，Youwei1; Kou，Lei1; Ke，Wende2; Wan，Junhe1; Yu，Zhen1; Liu，Hailin1; Zhang，Fangfang1

2024

10.3390/s24020444

Sensors   影响因子和分区

1424-8220

1424-8220

In order to realize the economic dispatch and safety stability of offshore wind farms, and to address the problems of strong randomness and strong time correlation in offshore wind power forecasting, this paper proposes a combined model of principal component analysis (PCA), sparrow algorithm (SSA), variational modal decomposition (VMD), and bidirectional long- and short-term memory neural network (BiLSTM). Firstly, the multivariate time series data were screened using the principal component analysis algorithm (PCA) to reduce the data dimensionality. Secondly, the variable modal decomposition (VMD) optimized by the SSA algorithm was applied to adaptively decompose the wind power time series data into a collection of different frequency components to eliminate the noise signals in the original data; on this basis, the hyperparameters of the BiLSTM model were optimized by integrating SSA algorithm, and the final power prediction value was obtained. Ultimately, the verification was conducted through simulation experiments; the results show that the model proposed in this paper effectively improves the prediction accuracy and verifies the effectiveness of the prediction model.

long- and short-term memory neural networks offshore wind farm power prediction sparrow algorithm variational modal decomposition

SCI ; EI

英语

其他

Chemistry ; Engineering ; Instruments & Instrumentation

Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation

WOS:001150794200001

MDPI

CHEMISTRY

2-s2.0-85183259720

Scopus

1.Institute of Oceanographic Instrumentation,Qilu University of Technology (Shandong Academy of Sciences),Qingdao,266075,China
2.Department of Mechanical and Energy Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Wang，Zhen,Ying，Youwei,Kou，Lei,et al. Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM[J]. Sensors,2024,24(2).

Wang，Zhen.,Ying，Youwei.,Kou，Lei.,Ke，Wende.,Wan，Junhe.,...&Zhang，Fangfang.(2024).Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM.Sensors,24(2).

Wang，Zhen,et al."Ultra-Short-Term Offshore Wind Power Prediction Based on PCA-SSA-VMD and BiLSTM".Sensors 24.2(2024).