| 基于相空间重构的神经网络短期风电预测模型 |
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| 引用本文： | 牛晨光,刘丛. 基于相空间重构的神经网络短期风电预测模型[J]. 中国电力, 2011, 44(11): 73-77 |
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| 作者姓名： | 牛晨光 刘丛 |
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| 作者单位： | 1. 华北电力大学电气与电子工程学院,河北保定,071003
2. 北京供电局,北京,100031 |
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| 摘 要： | 随着风电机组装机容量的持续高速增加以及大规模风电场的建设,各个国家(地区)的电网对风电的重视程度也在增加,风电场发电功率的短期预测对于风电场并网以及电网的调度起着至关重要的作用。通过对风电场发电功率的时间序列进行分析,表明该序列具有混沌属性,并在此基础上,利用相空间重构理论建立了关于风力发电功率的RBF神经网络与BP神经网络预测模型,并进行了实际预测。通过对结果进行对比分析,显示该模型可以得到较高的短期发电功率预测精度,更好地满足实际现场需要。
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| 关 键 词： | 混沌理论 相空间重构 短期风电功率预测 RBF神经网络 BP神经网络 |
Neural network model for short-term wind power prediction based on phase space reconstruction |
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| NIU Chen-guang,LIU Cong. Neural network model for short-term wind power prediction based on phase space reconstruction[J]. Electric Power, 2011, 44(11): 73-77 |
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| Authors: | NIU Chen-guang LIU Cong |
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| Affiliation: | NIU Chen-guang~1,LIU Cong~2 (1.School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China,2.Beijing Power Supply Bureau,Beijing 100031,China) |
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| Abstract: | With the lasting rapid increase of wind turbine capacity and the large-scale wind farm construction,the degree of recognition on wind power in different countries or regions' power grids is also increased.The short-term wind farm generation prediction plays an essential role for the wind farm access and power grid dispatch.the analysis on time series of wind farm generating capacity shows its chaos characteristic. Based on chaotic theory,phase space reconstruction method is used in RBF neural network and BP... |
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| Keywords: | chaotic theory phase space reconstruction short-term wind power prediction RBF neural network BP neural network |
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