| 电力短期负荷的多变量混沌预测方法 |
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| 引用本文： | 雷绍兰,孙才新,周湶,邓群,刘凡. 电力短期负荷的多变量混沌预测方法[J]. 高电压技术, 2005, 31(12): 69-72 |
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| 作者姓名： | 雷绍兰 孙才新 周湶 邓群 刘凡 |
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| 作者单位： | 重庆大学高电压与电工新技术教育部重点实验室,重庆,400031;重庆通信学院电力电子教研室,重庆,400035;重庆大学高电压与电工新技术教育部重点实验室,重庆,400031 |
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| 摘 要： | 为提高电力短期负荷预测精度和充分利用混沌短期预测优势,拓展单变量时间序列相空间重构到多变量时间序列中,相空间重构了由历史负荷及其相关因素序列所构成的多变量时间序列,计算了多变量时间序列的嵌入维数和延迟时间并用RBF神经网络预测负荷。研究表明多变量重构相空间技术的预测效果优于单变量重构。
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| 关 键 词： | 短期负荷预测 混沌 多变量时间序列 径向基函数神经网络 |
| 文章编号： | 1003-6520(2005)12-0069-04 |
| 收稿时间： | 2004-11-01 |
| 修稿时间： | 2004-11-01 |
Forecasting Method of Multivariate Time Series Applied in Short-term Electrical Load Forecasting |
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| LEI Shaolan,SUN Caixin,ZHOU Quan,DENG Qun,LIU Fan. Forecasting Method of Multivariate Time Series Applied in Short-term Electrical Load Forecasting[J]. High Voltage Engineering, 2005, 31(12): 69-72 |
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| Authors: | LEI Shaolan SUN Caixin ZHOU Quan DENG Qun LIU Fan |
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| Affiliation: | 1. The Key Laboratory of High Voltage Engineering and Electrical New Technology, Ministey of Education, Chongqing University, Chongqing 400031, China; 2. Chongqing Communication University, Chongqing 400035, China |
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| Abstract: | Univariate time series is extended to multivariate time series in order to improve the forecasting accuracy and to fully make use of superiority of chaotic short-term forecasting. At the same time, the phase space of multivariate time series is reconstructed, and embedding dimensions and delay time are calculated. Electrical load is forecasted by RBF net. Forecasting result shows the method is more effective than univariate time series. |
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| Keywords: | short-term load forecasting chaos multivariate time series RBF |
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