基于风速融合和NARX神经网络的短期风电功率预测  

Short-term wind power prediction based on wind speed fusion and NARX neural network

作　　者：徐遵义 王俊雪 XU Zunyi;WANG Junxue(Shandong Architecture University,Jinan 250101,China)

机构地区：[1]山东建筑大学,山东济南250101

出　　处：《现代电子技术》2020年第9期166-169,174,共5页Modern Electronics Technique

基　　金：济南市高校自主创新计划(201303001);山东省重点研发计划(2015GGX101047,2016GGX101024)。

摘　　要：高精度的短期风电功率预测是保证电网日常调度及运行安全的关键因素。目前,国内短期风电功率预测精度普遍低于国外水平。为了提高风机短期功率预测精度,提出一种基于风速融合和NARX神经网络的预测模型。该方法对同一地点不同数据源提供的预报风速进行融合,采用NARX神经网络进行短期风电功率预测。仿真实验结果表明,所提出的短期风电功率预测方法是可行的,预测精度可提高至87.8%,与其他风电功率预测模型相比,具有更高的预测精度和更好的适应性。High accuracy short-term wind power prediction is the key factor to ensure the daily dispatch and operation safety of power grid. At present,the accuracy of short-term wind power prediction in China is generally lower than that in foreign countries. In order to improve the short-term power prediction accuracy of fan,a prediction model based on wind speed fusion and NARX neural network is proposed in this paper. In the method,fusion of the forecasted wind speed is provided for different data sources at the same location,and NARX neural network is used for short-term wind power prediction. The simulation experiment results show that the short-term wind power prediction method proposed in this paper is feasible,and its prediction accuracy can be increased to 87.8%. In comparison with other wind power forecasting models,it has higher prediction accuracy and better adaptability.

关 键 词：短期风电功率预测 预测模型 NARX神经网络 风速融合 数据融合 数据处理 

分 类 号：TN99-34[电子电信—信号与信息处理] TP391[电子电信—信息与通信工程]