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

作　　者：茆美琴[1] 周松林[1] 苏建徽[1] 

机构地区：[1]合肥工业大学教育部光伏系统工程研究中心,安徽省合肥市230009

出　　处：《电力系统自动化》2011年第7期70-74,共5页Automation of Electric Power Systems

基　　金：国家重点基础研究发展计划(973计划)资助项目(2009CB219708)~~

摘　　要：对风电功率进行较为准确的预测是提高电力系统运行安全性与经济性的有效手段。在分析脊波神经网络原理的基础上,将其应用于风速、风向及风电功率预测。首先建立预测模型分别预测风速及风向,再采用非线性神经网络实现对实际功率曲线的逼近,最后根据风速预测值和实际功率拟合曲线计算功率预测值。仿真结果表明,采用脊波神经网络预测方法相对于小波神经网络、反向传播(BP)神经网络和径向基函数(RBF)神经网络方法,其风电功率预测结果准确性能得到提高。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 

分 类 号：TM614[电气工程—电力系统及自动化]