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电力短期负荷预测相似日选取算法
引用本文:黎灿兵,李晓辉,赵瑞,李金龙,刘晓光. 电力短期负荷预测相似日选取算法[J]. 电力系统自动化, 2008, 32(9): 69-73
作者姓名:黎灿兵  李晓辉  赵瑞  李金龙  刘晓光
作者单位:郑州大学电气学院,河南省郑州市,450001;北京电力公司调度中心,北京市,100031;华北电力大学电气与电子工程学院,北京市,102206
摘    要:短期负荷预测是电力系统安全经济运行的基础,相似日选取的准确与否直接影响到短期负荷预测算法的精度。针对短期负荷预测的特点,提出一种能便于考虑各种因素影响的新算法。分析了气象、日类型等因素对负荷影响的常见规律,便于识别主导负荷变化的因素,建立了在短期负荷预测中选取相似日的新方法。理论和实例均表明,该方法适应性较强,能够通过历史数据分析从历史日中选取最合适的相似日,对提高短期负荷预测的精度具有较大价值。

关 键 词:短期负荷预测  相似日  气象因素  累积效应
收稿时间:2008-01-02
修稿时间:2008-01-02

A Novel Algorithm of Selecting Similar Days for Short-term Power Load Forecasting
LI Canbing,LI Xiaohui,ZHAO Rui,LI Jinlong,LIU Xiaoguang. A Novel Algorithm of Selecting Similar Days for Short-term Power Load Forecasting[J]. Automation of Electric Power Systems, 2008, 32(9): 69-73
Authors:LI Canbing  LI Xiaohui  ZHAO Rui  LI Jinlong  LIU Xiaoguang
Abstract:Short-term load forecasting is the basis of safe and economical operation of power grids.The accuracy of selecting similar days directly influences the degree of accuracy of the short-term load forecasting algorithm.After an in-depth analysis of the common laws of such factors as the meteorological factors and the day type that impact power loads,a new algorithm of selecting similar days for the short-term load forecast is proposed.The algorithm can distinguish between the key factors in many cases.The simulation results demonstrate that it can select the most suitable similar day from a large number of historical data to improve the accuracy of short-term load forecasting with relatively strong adaptability.
Keywords:short-term load forecasting  similar day  meteorological factors  cumulative effect
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