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| 基于粗糙集和RBF神经网络的风电场短期风速预测模型 | |
| 引用本文： | 王莉,王德明,张广明,周献中. 基于粗糙集和RBF神经网络的风电场短期风速预测模型[J]. 南京工业大学学报(自然科学版), 2011, 33(6): 67-71. DOI: 10.3969/j.issn.1671-7627.2011.06.014 |
| 作者姓名： | 王莉 王德明 张广明 周献中 |
| 作者单位： | 1. 南京工业大学自动化与电气工程学院,江苏南京210009;南京大学工程管理学院,江苏南京210093 2. 南京工业大学自动化与电气工程学院,江苏南京,210009 3. 南京大学工程管理学院,江苏南京,210093 |
| 基金项目： | 江苏省科技厅工业科技支撑计划资助项目 |
| 摘 要： | 结合粗糙集提出了一种RBF神经网络短期风速预测模型。采用粗糙集对预测模型的输入特征空间进行约简,找出对未来预测的风速具有主要影响的因素,以此作为RBF神经网络预测模型的输入变量;在RBF神经网络训练的过程中,采用在线滚动优化策略,将最新的样本加入训练集,从而使预测模型能够跟踪风速的最新变化。将提出的方法用于某风电场的1 h短期风速预测,仿真实验结果表明该方法具有结构简单、预测精度高的优点。 |
| 关 键 词： | 风力发电 短期风速预测 粗糙集 RBF神经网络 |
Short-term wind speed prediction for wind farms based on rough sets and RBF neural network model |
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| WANG Li,WANG Deming,ZHANG Guangming,ZHOU Xianzhong. Short-term wind speed prediction for wind farms based on rough sets and RBF neural network model[J]. Journal of Nanjing University of Technology, 2011, 33(6): 67-71. DOI: 10.3969/j.issn.1671-7627.2011.06.014 | |
| Authors: | WANG Li WANG Deming ZHANG Guangming ZHOU Xianzhong |
| Affiliation: | 1.College of Automation and Electrical Engneering,Nanjing University of Technology,Nanjing 210009,China;2.School of Engineering and Management,Nanjing University,Nanjing 210093,China) |
| Abstract: | A radical basis function(RBF) neural network model combined with rough sets was used to predict short-term wind speed.Rough sets were used to reduce input feature space so that the significant factors for wind speed prediction could be found as the input variables of RBF neural network prediction model.Online rolling optimization was adopted in training RBF neural network.The latest sample was added into the training sets,thus the prediction model could catch recent changes of wind speed.The proposed method was used to predict wind speed in 1 h.Simulation results showed that the method had advantages of simplicity and high precision. |
| Keywords: | wind power generation short-term wind speed prediction rough sets RBF neural network |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |