基于灰色均生函数模型的电力系统月度负荷预测  

A Power System Monthly Load Forecasting Method Based on the Model of Grey-mean Generating Function

作　　者：穆钢[1] 郭鹏伟[1] 肖白[1] 刘青林[1] 杨士慧[1] 周潮[1] 张宇[1] 

机构地区：[1]东北电力大学微通电力系统研究室,吉林吉林132012

出　　处：《东北电力大学学报》2011年第3期1-6,共6页Journal of Northeast Electric Power University

摘　　要：首先使用历史负荷数据建立灰色GM(1,1)模型,并得到该历史负荷数据在GM(1,1)下的趋势值,其次通过历史负荷数据与趋势值的比值得到残余信息来构建均生函数模型,然后形成灰色均生函数模型(G-MGFM),最后提出了一种基于灰色均生函数模型的电力系统月度负荷预测方法。算例分析表明,与传统的预测模型相比,G-MGFM不仅建模过程简单,能够揭示电力负荷的发展趋势,而且更能描述其随机波动特性,较好地刻画电力负荷的发展变化规律;基于G-MGFM的负荷预测方法是有效可行的,其预测精度甚至好于使用线性回归模型(RAFM)和灰色理论模型(GFM)时的预测精度。This paper firstly set up GM（1,1） model using historical load data,and get the trend value of the historical load data under the GM（1,1） model;secondly,construct the mean generating function model applying the residual information,that is the ratio of the historical load data and trend value;and then set up the model of grey-mean generating function;finally,a power system monthly load forecasting method based on the model of grey-mean generating function is proposed.Analysis of typical calculation manifests that compared with the traditional forecasting model,the model of grey-mean generating function not only is modeled simply, and can reveal the trend of the development of electric power load,but also can describe the random wave characteristics of it,and depicts the change rule of the development of the electric power load.The method based on the model of grey-mean generating function is efficient and effective,and its prediction precision is even better than the linear regression model and the grey theory model.

关 键 词：电力系统 负荷预测 灰色GM(1 1)模型 均生函数 

分 类 号：TM744[电气工程—电力系统及自动化]