日能源需求和天气变量的小波分析

A. Bonkaney, I. Seidou Sanda, A. Balogun
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引用次数: 8

摘要

本文应用小波变换相干性(WTC)和相位分析方法分析了日电力需求(DED)与温度、相对湿度、风速和辐射等天气变量之间的关系。DED数据呈现季节波动和增加趋势,而天气变量仅描述季节变化。从WTC和相位分析得到的结果使我们能够探测到DED与天气变量显著相关的时间段。我们发现气温与DED之间存在很强的季节相关性,周期性为256 ~ 512天和128 ~ 256天。在平均相干度为0.8的周期(256 ~ 512 d)内,湿度与DED之间也表现出显著的相互依赖关系。辐射与风速相关性较低,平均相干度小于0.5。这些结果提供了对天气变量对电力需求影响特性的深入了解,在此基础上,电力规划者可以依靠这些变量来改进他们对电力需求的预测和规划。
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Wavelet Analysis of Daily Energy Demand and Weather Variables
In this paper, we applied the Wavelet Transform Coherence (WTC) and phase analysis to analyze the relationship between the daily electricity demand (DED) and weather variables such as temperature, relative humidity, wind speed, and radiation. The DED data presents both seasonal fluctuations and increasing trend while the weather variables depict only seasonal variation. The results obtained from the WTC and phase analysis permit us to detect the period of time when the DED significantly correlates with the weather variables. We found a strong seasonal interdependence between the air temperature and DED for a periodicity of 256-512 days and 128-256 days. The relationship between the humidity and DED also shows a significant interdependence for a periodicity of 256-512 days with average coherence equal to 0.8. Regarding the radiation and wind speed, the correlation is low with average coherence less than 0.5. These results provide an insight into the properties of the impacts of weather variables on electricity demand on the basis of which power planners can rely to improve their forecasting and planning of electricity demand.
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审稿时长
28 weeks
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