电力系统保护与控制2016，Vol.44Issue(12)：63-67,5.DOI:10.7667/PSPC151217
基于马尔可夫链筛选组合预测模型的中长期负荷预测方法
Mid-long term load forecasting based on Markov chain screening combination forecasting models
摘要
Abstract
It is important to choose theright model according to thetrend of the historical data in the process of load forecast model combination.And then, a method is chosen to assign weights according to thefeaturesof the models.Even forecast models meetthe requirements of the grey correlation degree, theforecast results stillhave large differences. To solve the question, this paper, according to the feature that the growth rate of load data isnon-aftereffect property of Markov chain, and byanalyzingthegrowth rate of load data, usesMarkov chain to divideintervals andscreens two kinds from the models which havemet theaccuracyrequirement, and adopts the method ofvariance-covariance toassign weights. Using this method of screening not only canaccurately choose the models forcombination forecast, but also has a high precision.关键词
马尔可夫链/筛选/灰色关联度/组合预测Key words
Markov chain/screen/grey relational degree/combination forecast引用本文复制引用
张栋梁,严健,李晓波,任晓达,张金忠,张福来..基于马尔可夫链筛选组合预测模型的中长期负荷预测方法[J].电力系统保护与控制,2016,44(12):63-67,5.基金项目
国家自然科学基金(51107143)This work is supported by National Natural Science Foundation ofChina (No.51107143) （51107143）
