| 基于混沌时间序列的大型风电场发电功率预测建模与研究 |
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| 引用本文： | 冬雷,王丽婕,高爽,廖晓钟.基于混沌时间序列的大型风电场发电功率预测建模与研究[J].电工技术学报,2008,23(12). |
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| 作者姓名： | 冬雷 王丽婕 高爽 廖晓钟 |
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| 作者单位： | 1. 北京理工大学信息科学技术学院,北京,100081;北京理工大学复杂系统智能控制与决策教育部重点实验室,北京,100081
2. 北京理工大学信息科学技术学院,北京,100081 |
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| 基金项目： | 国家自然科学基金资助项目
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| 摘 要： | 通过对风力发电系统的发电功率时间序列进行低维非线性动力学建模,表明该时间序列呈现混沌特性。在此基础上,利用混沌时间序列的相空间理论建立了风力发电功率神经网络预测模型,对风力发电功率的短期预测进行了分析和研究,并得到了较高的精度。本文研究数据均来自大唐赛罕坝百万千瓦级风电场。
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| 关 键 词： | 风力发电 混沌属性 功率预测 神经网络 |
Modeling and Analysis of Prediction of Wind Power Generation in the Large Wind Farm Based on Chaotic Time Series |
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| Dong Lei,Wang Lijie,Gao Shuang,Liao Xiaozhong.Modeling and Analysis of Prediction of Wind Power Generation in the Large Wind Farm Based on Chaotic Time Series[J].Transactions of China Electrotechnical Society,2008,23(12). |
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| Authors: | Dong Lei Wang Lijie Gao Shuang Liao Xiaozhong |
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| Affiliation: | Beijing Institute of Technology Beijing 100081 China |
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| Abstract: | The time series of wind power generating capacity are examined by nonlinear dynamical methods, in order to identify chaos characteristic from its random-like waveform. The analysis of modeling with low dimensions nonlinear dynamics indicates that time series of wind power generating capacity have chaos characteristic, and wind power generating capacity can be predicted in short time. Phase space reconstruction method is used for artificial neural network model design. The data from the wind farm located in the Saihanba China are used for this study. |
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| Keywords: | Wind power generation chaos characteristic capacity prediction neural network |
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