基于相似日和灰色理论的短期电力负荷预测研究

Research on Short Term Power Load Forecast Based on Similar Day and Grey Theory

针对短期电力负荷预测易受气象因素影响的特点,提出基于相似日和灰色理论的短期电力负荷预测模型;首先通过对日类型的判断得到相同日类型的负荷数据,然后对气象数据序列进行模糊化聚类处理,并结合预测日的气象数据,采用灰色关联方法进行关联分析,选取与预测日关联度高的负荷数据作为相似日负荷数据,采用灰色预测方法对相似日负荷数据进行短期电力负荷预测;仿真结果表明,选取了相似日之后的预测结果比未选取相似日的预测结果精度要高。

According to the feature that short term power load is susceptible to meteorological factors, this paper proposes short term power load forecasting model based on similar day and grey theory, firstly tries to get the load data at the same day through the judgment on day type, then deals with the meteorological data sequence by fuzzy clustering analysis, uses the meteorological data at forecasting day and grey correlation method to conduct correlation analysis, chooses the load data which are highly correlated with forecasting day as the load data at similar day, and uses grey forecasting method to forecast short term power load based on similar day load data. Simulation results show that the accuracy of forecasting results is higher after the selection of similar day than without the selection of similar day.