基于最优组合预测模型的电力负荷预测研究  

Research on the Forecast of Electric Power Load Based on Optimal Combination Prediction Model

作　　者：王蒙[1] 张国友[1] 田丽[1] 周明龙[1] 王静[1] 

机构地区：[1]安徽工程大学电气工程学院,安徽芜湖241000

出　　处：《重庆工商大学学报（自然科学版）》2012年第9期65-69,共5页Journal of Chongqing Technology and Business University:Natural Science Edition

基　　金：国家自然科学基金(71171002);安徽省自然科学基金(11040606M24)

摘　　要：电力负荷预测是电力规划及安全运行的基础,提高预测精度是电力负荷预测研究的重点,由于负荷预测的变化性和不确定性,单一的预测模型很难满足所有的预测情况;组合预测是将各个单项预测所得的结果选取适当的权系数进行加权平均的一种预测方法;采用灰色和时间序列作为单项预测模型,然后进行最优组合建立组合预测模型进行电力系统短期负荷预测;仿真实例表明:最优组合预测模型比单项预测模型具有更高的预测精度,具有一定的优越性。Electric power load forecast is the basis for the planning and safe operation of electric power,and the improvement of forecast accuracy is the important point for the research on electric power load forecast.Because of the changeable characteristics and uncertainty of load forecast,single forecast model is difficult to satisfy all forecast conditions and combined forecast is a kind of forecast method by using prediction results from each prediction to choose appropriate weight and coefficient for weighted average.Grey and time-series are used in single prediction model,then combined prediction model is set up by optimal combination for short-term load prediction of electric power system and simulation experiment shows that optimal combination prediction model has higher prediction accuracy than single prediction model and has certain advantage.

关 键 词：负荷预测 组合预测 加权平均 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]