电力系统自动化2011，Vol.35Issue(7)：70-74,5.
基于脊波神经网络的短期风电功率预测
Short-term Wind Power Forecast Based on Ridgelet Neural Network
摘要
Abstract
Fairly accurate forecast of wind power is an effective means for improving power system security and economy. Based on an analysis of the principle of the ridgelet neural network, the network is applied to the forecast of wind speed, wind direction and wind power. Two forecast models are developed to predict wind speed and wind direction, respectively, and the nonlinear neural network is applied to the approximation of an actual power curve. Finally, the wind power is calculated according to the forecasted wind speed, wind direction and the power fitting curve. Simulation results show that, compared with the wavelet neural network, BP neural network and RBF neural network, the ridgelet neural network is found to yield a higher accuracy of wind power forecast than all the other three.关键词
风电功率预测/脊波神经网络/非点状奇异性/功率曲线/泛化性能Key words
wind power forecast/ridgelet neural network/non-point-like singularity/power curve/generalization performance引用本文复制引用
茆美琴,周松林,苏建徽..基于脊波神经网络的短期风电功率预测[J].电力系统自动化,2011,35(7):70-74,5.基金项目
国家重点基础研究发展计划(973计划)资助项目(2009013219708). （973计划）
