摘要
为提高月售电量预测准确度,引入TRAMOS-SEATS季节调整方法和Hodrick-Prescott滤波法将月售电量分解为趋势分量、季节分量、循环分量和不规则分量,消除了各分量之间的相互影响。采用ARIMA方法对趋势分量进行预测,采用Holt-Winters加法模型对季节分量进行预测,采用历史同期同类平均值法对循环分量和不规则分量进行预测,最后得到月售电量预测结果。应用实际算例对月售电量进行预测并与实际数据进行对比,验证法方法的正确性与有效性。
To improve the accuracy of monthly electricity sales forecasting,the TRAMO-SEATS seasonal adjustment method and Hodrick-Prescott Filter are applied to decompose monthly electricity sales into trend component, seasonal component,cyclical component and irregular component,in which the mutual influence between each component can be eliminated. The ARIMA method is used to forecast the trend component,the Holt-Winters addictive method the seasonal component and the similar historical average method the cyclical component and irregular component so as to finally achieve the forecasting results of monthly electricity sales. The actual case is used to prove the correctness and effectiveness of the method by comparingtheforecastingmonthlyelectricitysalesandactualsales.
作者
张永凯
马欢
ZHANG Yongkai;MA Huan(State Grid Shandong Electric Power Co., Ltd., Jinan Electric Power Company, Jinan 250012,Shandong, China)
出处
《电网与清洁能源》
2018年第2期72-78,共7页
Power System and Clean Energy
基金
中央高校基本科研业务费专项资金资助(xjj2015034)~~