超过指数增长速度的年度用电量曲线拟合预测

为有效预测超过指数增长速度的年度用电量，选用超阶乘、二重指数等可线性化的函数，对年度用电量进行曲线直接拟合外推预测．采用这些新的数学函数预测北京年度用电量，拟合平均相对误差绝对值小于4．2%,2006年校验误差小于1．9％．超阶乘、二重指数函数不仅可用于超过指数增长的负荷预测，还可用于纠正线性回归、指数平滑和移动平均等方法对增长负荷预测值偏小的系统误差

Forecasting Annual Electricity Consumption of Ultra-Exponent Increase Trend by Curve Fitting

To forecast the annual electricity consumption of ultra-exponent increase trend,linearizing mathematical functions,such as ultra-factorial and duplicate-exponent,were adopted to directly fit the historical loads and forecast the future annual loads.Using these new functions to fit the historical data,the mean relative percentage error is less than 4.2%,and forecast error of the year of 2006 is less than 1.9% for the annual electricity consumption of Beijing.Besides forecasting the annual electricity consumption of ultra-exponent increase trend accurately,the functions of ultra-factorial and duplicate-exponent can be used to rectify the systematic errors in increasing load forecasting by linear regression,exponential smoothing and moving average.