Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions

王 宝; 马 静; 叶 斌; 杨 敏; 卢金滇; 李亚玲

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Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions

更新时间：2026-03-05

- Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions
- Vol. 22, Issue 2, (2020)
- 作者机构：
  
  1. 国网安徽省电力有限公司经济技术研究院,合肥,230022
  2. 国网安徽省电力有限公司,合肥,230061
  3. 国网安徽省电力有限公司六安供电公司,安徽,六安,237000
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2020
- 稿件说明：
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王宝, 马静, 叶斌, et al. Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions[J]. 2020, 22(2).
DOI：

王宝, 马静, 叶斌, et al. Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions[J]. 2020, 22(2). DOI：

摘要

当前，经济新常态和极端天气频发使得电力需求影响因素更加多样化，而用电量和最大负荷等电力需求指标缺乏科学的一体化预测方法。系统分析了电力需求的经济与气象维度主要影响因素，并构建了一套基于经济与气象维度影响因素的省级电网年度电力需求预测模型体系。实例分析表明，无论基于多元线性回归还是智能算法工具构建预测模型，提高预测准确度的核心是识别关键的影响因素。模型系统对用电量和最大负荷预测的平均误差率均处于2%以内的合理水平，是电力市场分析预测人员开展年度电力需求预测工作的一种有效方法。

Abstract

Currently

economic new normal and frequent extreme weather make influencing factors of power demand more diversified. Forever

integrated forecast methods of such two power demand indicators as power consumption and max power load arenot scientifically formed. Main influencing factors of power demandfrom economic and meteorological dimensions are systematicallyanalyzed and a forecast model system of provincial grid’s annualpower demand is established. The instance of Anhui province demonstrates that the key of improving forecast accuracy is to identify critical influencing factors regardless of basing forecast model on multiple linear regression or intelligent algorithm. Mean forecast error rates of power consumption and max power load remain are both within 2% in this model

becoming an effective method for electricity market analysts to forecast annual power demand.

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