基于相似模型泛函时间序列的短期电力负荷预测

Short Time Load Prediction Based on Similar Shape Functional Time-Series

采用一种新型的泛函时间序列方法预测短期电力负荷,建立一种历史日分段负荷与预测分段负荷相似模型的加权平均关系,根据实际观测的分段负荷与参考的分段负荷之间的贴近度,从历史数据中辨识出历史分段负荷,进而通过这种方法捕获需要预测的负荷特性和量化特征。为便于比较说明,将所提泛函时间序列方法应用于某地区的历史日负荷数据,并与近年文献中提出的类似方法进行了比较,证明了本文所提短期负荷预测方法的可行性。

A novel functional time-series methodology for short term load forecasting is introduced. The prediction is performed by means of a weighted average of past daily load segments,the shape of which is similar to the expected shape of the load segment to be predicted. The past load segments are identified from the available history of the observed load segments by means of their closeness to a so-called reference load segment. The latter is selected in a manner that captures the expected qualitative and quantitative characteristics of the load segment to be predicted. As an illustration, the suggested functional time-series forecasting methodology is applied to historical daily load data in a certain area. Its performance is compared with some recently proposed alternative methodologies for short-term load forecasting, the feasibility of proposed method is proved.