基于相空间重构及自适应支持向量机的短期风速预测

风速具有较强的随机性和间歇性，导致大规模风电接入电网会严重影响电力系统的安全稳定运行以及电能质量。较为准确的风速预测可以降低风能对电网的不利影响，为电网运行调度提供可靠的依据。在对风速进行混沌属性分析及相空间重构的基础上，采用自适应支持向量机进行短期风速预测，结果表明该方法的预测精度高于BP、RBF等预测模型。

Short-term Wind Speed Forecasting Based on Phase Space Reconstruction and Self-Adaptive Support Vector Machine

The wind is strong random and intermittent, which leads to large scale wind power integration will seriously affect the safe and stable operation of power system and power quality. Wind speed and more accurate prediction can reduce the adverse impact of wind power on the grid, and provide reliable basis for power griddispatching. Based on the chaotic property analysis of wind speed and phase space reconstruction, using adaptive short-term wind speed forecasting support vector machine, the results indicate that the prediction accuracy of this method is higher than that of BP, RBF prediction model.