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基于混沌时间序列的负荷预测及其关键问题分析
LOAD FORECASTING BASED ON CHAOTIC TIME SERIES AND ANALYSIS OF ITS KEY FACTORS
【摘要】 通过对混沌时间序列进行分析,找出了运用它进行电力系统负荷预测的关键因素:“取舍规则”、嵌入维数和延时的选取。笔者还建立了一种“取舍规则”,并运用它进行了实例分析,结果表明基于该“取舍规则”进行负荷预测的效果良好。
【Abstract】 Through the analysis of chaotic time series, two key factors used in power system load forecasting are found, i.e., the rule of acceptance and rejection and the selection of embedded dimensions and time delay. On this basis another kind of acceptance and rejection is proposed and applied in the analysis of practical examples. The analysis results show that the load forecasting based on the proposed rule of acceptance and rejection is more accurate.
【关键词】 电力系统;
负荷预测;
取舍规则;
混沌时间序列;
嵌入维数;
延时;
Lyapunov指数;
【Key words】 Power system; Load forecasting; Rule of acceptance and rejection; Chaotic time series; Embedded dimensions; Time delay; Lyapunov index;
【Key words】 Power system; Load forecasting; Rule of acceptance and rejection; Chaotic time series; Embedded dimensions; Time delay; Lyapunov index;
【基金】 高等学校博士学科专项科研基金资助项目(2000048712);华中科技大学研究生基金资助项目
- 【文献出处】 电网技术 ,Power System Technology , 编辑部邮箱 ,2004年13期
- 【分类号】TM715
- 【被引频次】64
- 【下载频次】520