基于海上风电功率特性的预测误差对比分析

Prediction of offshore wind power is a prerequisite for the stable operation of large-scale wind farms. The accuracy of wind power prediction plays an important role in improving the quality and consistency of the power grid.To improve the wind power prediction error, the Auto Regressive Integrated Moving Average(ARIMA)and the improved k-Nearest Neighbor(kNN)method were used to predict the offshore wind power. Results show that wind power could be predicted by different prediction techniques according to different characteristics, the prediction error was less than 20%, and the prediction accuracy could be improved by improving the prediction method. Finally, the improved two prediction methods were verified by a specific example, and the results were compared to verify the effectiveness of the algorithm.