电测与仪表Issue(22)：30-34,5.
基于灰色神经网络优化组合的风力发电量预测研究
Study on Wind Power Capacity Prediction Based on the Optimal Combination of the Grey Neural Network
摘要
Abstract
This paper proposed a study on wind power capacity prediction based on the optimal combination of the grey neural network,which combined the artificial neural network( ANN)prediction model with the grey prediction model effectively. This study not only considered such factors as wind velocity,wind direction and temperature,but also took into account the historical data of the wind power capacity in the previous years. The combination of the advantages of both predictions improved the prediction accuracy and reduced the prediction errors. The results of the calculation ex-ample proved that the forecasting value error of the grey neural network optimal combination was lower than that of the single grey prediction or neural network prediction.关键词
人工神经网络/灰色预测技术/优化组合预测技术/误差/风力发电量Key words
artificial neural network/grey prediction model/optimal combination forecasting technique/error/wind分类
信息技术与安全科学引用本文复制引用
章勇高,王妍,孙佳,高彦丽..基于灰色神经网络优化组合的风力发电量预测研究[J].电测与仪表,2014,(22):30-34,5.基金项目
江西省教育厅科技项目（GJJ14387）；江西省科技厅科技攻关项目 （）
