计算机工程与应用2016，Vol.52Issue(12)：265-270,6.DOI:10.3778/j.issn.1002-8331.1408-0018
EMD与NARX神经网络的风电场总功率组合预测
Novel total-power combinational forecasting method of wind farm based on EMD and NARX neural network
摘要
Abstract
A high-precision combinational method is presented to forecast the total-power of wind farm directly. Taking into account that the Non-stationary identity of wind speed leads to the non-stationary time series of total-power, the NARX neural network is adopted as the original forecasting model. And then, a hybrid forecasting method based on Empirical Mode Decomposition(EMD)and NARX neural network is proposed to improve the forecast precision. First, the total-power time series is decomposed into several stable trend terms with different Intrinsic Mode Functions(IMF). Subsequently, the corresponding prediction models of NARX neural network are set up according to different stable components. These forecasting results of each component model are summed up in equal weight to obtain the final predictive value. Besides, the data of time intervals of 5-minute and 15-minute obtained from a large wind power plant are used in the experiments to explore how time intervals affect the predictive results. The experiment shows that the combinational model is suitable for the prediction of total-power. According to the experimental results, the combinational model is more accurate than many traditional methods, and the prediction accuracy of 5-minute time interval data is more accurate than that of 15-minute time interval data.关键词
经验模态分解/非线性自回归神经网络(带外部输入的)(NARX)/非平稳时间序列/风电场/总功率Key words
empirical mode decomposition/Nonlinear Auto-Regressive with eXogenous input neural network(NARX)/non-stationary time series/wind power/total power分类
信息技术与安全科学引用本文复制引用
张振华,马超,徐瑾辉,欧阳泽拯..EMD与NARX神经网络的风电场总功率组合预测[J].计算机工程与应用,2016,52(12):265-270,6.基金项目
国家自然科学基金（No.71271061）；中国大学生创新训练计划项目（No.201411846001，No.201411846013）；广东省教育厅科技创新项目（No.296-GK13201，No.2013KJCX0072）；广东省质量工程项目（No.110-GK131021）；广东省十二五教育规划项目（No.2012JK129）；广东省十二五哲学社科项目（No.GD12XGL14）；广州市哲学社科项目（No.2014GZZXGJ0067）；广东外语外贸大学重点团队项目（No.TD1202）；广东外语外贸大学教学改革重点项目（No.GYJYZDA12011）。 （）
