首页> 外文期刊>Journal of tropical meteorology >THE VARIABILITY CHARACTERISTICS AND PREDICTION OF GUANGDONG POWER LOAD DURING 2002 - 2004
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THE VARIABILITY CHARACTERISTICS AND PREDICTION OF GUANGDONG POWER LOAD DURING 2002 - 2004

机译:广东省2002年-2004年电力负荷的变化特征及预测。

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摘要

The variability characteristics of Guangdong daily power load from 2002 to 2004 and its connection to meteorological variables are analyzed with wavelet analysis and correlation analysis. Prediction equations are established using optimization subset regression. The results show that a linear increasing trend is very significant and seasonal change is obvious. The power load exhibits significant quasi-weekly (5-7 days) oscillation, quasi-by-weekly (10 - 20 days) oscillation and intraseasonal (30 - 60 days) oscillation. These oscillations are caused by atmospheric low frequency oscillation and public holidays. The variation of Guangdong daily power load is obviously in decrease on Sundays, shaping like a funnel during Chinese New Year in particular. The minimum is found at the first and second day and the power load gradually increases to normal level after the third day during the long vacation of Labor Day and National Day. Guangdong power load is the most sensitive to temperature, which is the main affecting factor, as in other areas in China. The power load also has relationship with other meteorological elements to some extent during different seasons. The maximum of power load in summer, minimum during Chinese New Year and variation during Labor Day and National Day are well fitted and predicted using the equation established by optimization subset regression and accounting for the effect of workdays and holidays.
机译:通过小波分析和相关分析,分析了2002〜2004年广东省日用电负荷的变化特征及其与气象变量的联系。使用优化子集回归建立预测方程。结果表明,线性增长趋势非常明显,季节变化明显。电力负荷表现出显着的准每周(5-7天)振荡,准每周(10-20天)振荡和季节内(30-60天)振荡。这些振荡是由大气低频振荡和公众假期引起的。周日,广东日用电负荷的变化明显减少,尤其是农历新年期间的漏斗状。在第一天和第二天发现最小值,在劳动节和国庆日的长假期间,电力负荷在第三天之后逐渐增加到正常水平。与中国其他地区一样,广东电力负荷对温度最敏感,温度是最主要的影响因素。在不同季节,电力负荷也与其他气象要素有一定关系。通过优化子集回归并考虑工作日和节假日的影响,可以很好地拟合和预测夏季的最大电力负荷,农历新年期间的最小负荷以及劳动节和国庆节期间的变化。

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