基于马尔科夫修正的电力系统超短期负荷灰色预测  

Ultra-short Term Load Forecasting Based on Grey Theory and Markov Chain

作　　者：钱虹[1,2] 阮大兵[1] 黄正润[1] 费敏锐[2] 

机构地区：[1]上海电力学院,上海200090 [2]上海大学,上海200072

出　　处：《华东电力》2013年第5期1023-1026,共4页East China Electric Power

基　　金：上海市教育委员会重点学科建设项目资助(J51303)~~

摘　　要：针对目前超短期负荷预测在拐点处预测误差较大,提出了根据时间序列相似的拐点预测方法。算法首先运用平滑处理方法对历史数据预处理,得出负荷序列的总体趋势,再运用灰色理论模型预测负荷变化平稳时段的负荷。介绍了运用马尔科夫链统计方法对随机部分的修正。Given that large errors often occur at inflection point during the ultra-short term load forecasting at parent, this paper presents a forecasting method for similar inflection point in terms of the time series. After smoothing pro- cessing of the historical data, general trend of the power load can be obtained; then grey theory is adopted to fit the trend when the power load changes steadily. Finally, Markov Chain is employed to modify the random part of the pow- er load.

关 键 词：超短期负荷预测 灰色理论 马尔科夫链 平滑处理 拐点预测 

分 类 号：TM732[电气工程—电力系统及自动化]