基于EMD的时标特征提取方法及其在短期电力负荷预测中的应用

Time-scale feature extraction based on EMD and its application on short-term power load forecasting

为凸显负荷波动的随机性、周期性和相关趋势,通过探求负荷变化机理显著提升预测精度,提出了一种基于EMD的负荷波动机理研究方法。首先对负荷进行EMD分解,得到随机、周期和趋势分量;然后分析各分量的变化规律与候选影响因素的关联关系,推导负荷变化机理,提取时标特征值;最后进行特征的去冗余。该方法创新点是能提取出特征值的时标特性。以广东省负荷数据集作为预测案例研究,对比实验研究结果表明了所提方法的有效性。

In order to highlight the randomness,periodicity and related trend of load fluctuation,and further improve the prediction accuracy,this paper proposed a prediction method based on EMD and load fluctuation mechanism.Firstly,it decomposed the EMD of the load to obtain the random component,the periodic component and the trend component.Secondly,it analyzed the correlation between the variation rule of each component and the candidate factor.It deduced the load fluctuation mechanism,and extracted the characteristic value of the load forecasting time.Finally,it de-redundanted the feature.It extracted the novelty of this method was that the time scale characteristic of feature.Taking the load data set of Guangdong Province as a case study,the experimental results show that the proposed method is effective.