电信科学 ›› 2019, Vol. 35 ›› Issue (3): 127-134.doi: 10.11959/j.issn.1000-0801.2019041

• 电力信息化专栏 • 上一篇    下一篇

考虑春节影响的售电量预测结果修正方法

刘建1,赵加奎1,陈雨泽1,方学民2,刘玉玺1,王树龙1,陈雁1,欧阳红1   

  1. 1 国网信息通信产业集团有限公司,北京 100085
    2 国家电网有限公司,北京 100032
  • 修回日期:2019-01-20 出版日期:2019-03-01 发布日期:2019-03-23
  • 作者简介:刘建(1989- ),男,国网信息通信产业集团有限公司工程师,主要研究方向为电力营销大数据分析。|赵加奎(1979- ),男,博士,国网信息通信产业集团有限公司教授级高级工程师,主要研究方向为电力信息化及电力大数据分析。|陈雨泽(1988- ),男,国网信息通信产业集团有限公司工程师,主要研究方向为电力营销大数据分析。|方学民(1972- ),男,国家电网有限公司高级工程师,主要研究方向为电力信息化及电力大数据分析。|刘玉玺(1984- ),男,国网信息通信产业集团有限公司高级工程师,主要研究方向为电力信息化及电力大数据分析。|王树龙(1978- ),男,国网信息通信产业集团有限公司工程师,主要研究方向为电力营销信息化及大数据分析。|陈雁(1981- ),女,博士,国网信息通信产业集团有限公司高级工程师,主要研究方向为电力营销大数据分析、人工智能技术研究与应用。|欧阳红(1967- ),男,国网信息通信产业集团有限公司高级工程师,主要研究方向为电力信息化及电力大数据分析。

An adjustment method for electricity sales forecasting result considering the effects of spring festival

Jian LIU1,Jiakui ZHAO1,Yuze CHEN1,Xuemin FANG2,Yuxi LIU1,Shulong WANG1,Yan CHEN1,Hong OUYANG1   

  1. 1 State Grid Information &Telecommunication Group Co.,Ltd.,Beijing 100085,China
    2 State Grid Corporation of China,Beijing 100032,China
  • Revised:2019-01-20 Online:2019-03-01 Published:2019-03-23

摘要:

考虑春节对不同行业的影响,提出了一种考虑春节因素影响的月度售电量预测结果修正方法,首先利用历史春节日期距1—3月第一天的天数和历史各行业1—3月的售电量占第一季度售电量的占季比进行曲线拟合,然后利用预测年份春节日期距1—3月第一天的天数和拟合函数计算预测年份1—3月售电量占季比的预测值,最后利用各月占季比预测值对国家电网公司1—3月的售电量预测结果进行修正,得到春节因素修正后的售电量预测结果。实证研究结果表明,本文提出的售电量预测结果修正方法能够有效地降低第一季度售电量预测误差。

关键词: 售电量, 春节, 回归分析, 最小二乘法

Abstract:

The effects of Spring Festival on electricity sales of different trades were considered and an adjustment method for electricity sales forecasting result was proposed.Firstly,the month-quarter ratio of historical electricity sales in each trade of every month in the first quarter and the distance between Spring Festival and the first day of every month in the first quarter was used to create a functional relationship.Then,the distance between Spring Festival and the first day of every month in the first quarter of the target year was used as input and the predicted month-quarter ratio of electricity sales of each trade of every month in the first quarter of the target year was calculated according to the functional relationship.The adjusted electricity sales forecasting result can then be computed by using the predicted month-quarter ratio and the electricity sales forecasting of each trade of every month in the first quarter of the target year before adjustment.The adjustment result shows that the proposed method can effectively lower the error of electricity sales forecasting in the first quarter.

Key words: electricity sales, Spring Festival, regression analysis, least square

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