电源技术Issue(12)：2328-2330,2369,4.
基于混沌径向基函数的风电功率短期预测
Prediction of short-term wind power based on chaotic RBF
摘要
Abstract
There were two kinds of method to predict the wind power, which were the direct forecasting method and the power curve conversion forecasting method. The wind speed and the wind power were predicted with the theories related to the chaotic time series because the wind power was chaotic. First the parameters of the phase-space reconstruction were optimized by C-C method because the accuracy of the prediction largely depended on the parameters used; then the wind power was predicted by the RBF neural network. The predicted wind power could also be achieved based on the curve of wind turbines after the wind speed was predicted by the RBF neural network. The analysis of the example shows that both of the methods have good performances in accuracy and the direct way based on the chaotic RBF neural network is better than the other one.关键词
风电功率/短期预测/混沌特性/相空间重构/C-C法/直接预测法/功率曲线转换法/RBF神经网络Key words
wind power/short term prediction/chaotic property/phase-space reconstruction/C-C method/direct forecasting method/power curve conversion forecasting method/RBF neural network分类
信息技术与安全科学引用本文复制引用
李玲玲,李宗礼,李俊豪,李志刚..基于混沌径向基函数的风电功率短期预测[J].电源技术,2014,(12):2328-2330,2369,4.基金项目
国家自然科学基金(51377044，51475136)；高等学校博士学科点专项科研基金(20121317110008)；河北省建设科技研究计划项目(2011-147) （51377044，51475136）
