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

作　　者：张步涵[1] 刘小华[2] 万建平[2] 刘沛[1] 程时杰[1] 

机构地区：[1]华中科技大学电气与电子工程学院,湖北省武汉市430074 [2]华中科技大学数学系,湖北省武汉市430074

出　　处：《电网技术》2004年第13期32-35,49,共5页Power System Technology

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

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。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 混沌时间序列 非线性动力系统 

分 类 号：TM715[电气工程—电力系统及自动化]