多元指数加权电力负荷灰色优化组合预测

由于电力负荷具有增长性和波动性并且受到多个因素影响,使得电力负荷的变化呈现出复杂的多元性及非线性组合特性,对于这种具有复杂的多元性及非线性组合特性的序列,使用传统的模型进行预测,预测精度往往不理想.为了提高预测精度,作者为提出了多元指数加权电力负荷灰色优化组合预测模型.其中灰色优化组合预测模型用于进行非线性增长趋势的电力负荷预测,指数加权法能解决历史负荷的波动性问题.实际算例表明,所提出的方法由于综合考虑了电力负荷的多种特性,能有效地提高负荷预测精度.

RESEARCH ON GRAY OPTIMIZATON COMBINATION POWER LOAD FORECASTING BASED ON MULTIVARIATE EXPONENTIAL WEIGHTING

Because power loads possess the features of increment and seasonal fluctuation and are influenced by various factors, so the change of power load presents complicated and non-linear combination character. When traditional forecasting models are applied to such a complicated load series, the forecasting accuracy is always not satisfied. To improve the forecasting accuracy, the authors proposed a new multivariable exponential weighting based gray optimal combination model to forecast the power loads, in which the gray optimal combination model was used to forecast the power loads with non-linear increasing trend and the multivariable exponential weighting method was used to solve the fluctuation of historical load data. Case calculation results show that the proposed method, in which various features of power loads are considered, can; effectively improve the accuracy of load forecasting.