气象因素对淮北市电力负荷的影响及其预测研究

利用2012—2016年安徽省淮北市逐日用电负荷和气象要素数据，采用相关分析、回归分析、曲线拟合等统计方法，分析用电负荷的季节变化、周末/节假日效应变化规律，提炼主要气象影响因子并分析温度对负荷的1℃效应和负荷对最高温度的敏感性，构建趋势负荷和趋势方程，介绍将周末/节假日效应应用于气象负荷提取和不同预测模型的建立，采用趋势法建立逐日负荷预测的多元回归方程和曲线拟合方程，并针对趋势法的弱点提出2日增量法，建立相应的预测模型，其中2日增量法预测模型的历史拟合率和2017年试报应用均达到96%—97%，比趋势法高2%—3%，比目前的考核要求高4%—5%，提高了负荷预测精度。

Effects of meteorological factors on electrical load and the forecasting of electrical load

Using the daily electrical load and meteorological data of Huaibei in Anhui province from 2012 to 2016, statistical methods such as correlation analysis, regression analysis, and curve fitting were used to analyze the seasonal variation and weekend/holiday effect of electrical load.Main meteorological influence factors were extracted.The effect of temperature (1 ℃) on electrical load and the sensitivity of electrical load to maximum temperature were also analyzed.The trend load and trend equation were determined in this study.The methods of applying weekend/holiday effects to different forecasting models and scientific methods of extracting meteorological load were introduced.The multivariate regression equation and curve-fitting equation of daily electrical load forecasting were established using the trend method.Considering the weakness of the trend method, a 2-day increment method was proposed.The corresponding forecasting model was established.Among them, the historical fitting rate of the 2-day increment forecasting model and the accuracy of the trial forecasting in 2017 both reach 96%-97% which is 2%-3% higher than those with the trend method, and 4%-5% higher than the current assessment requirements.In conclusion, a 2-day increment method improves the accuracy of electrical load forecasting.