基于马尔科夫链改进无偏灰色Verhulst的中长期负荷预测模型  

Long term load forescasting model based on markov chain improving unbiased grey Verhulst

作　　者：张宁[1] 黄伟琼 

机构地区：[1]福州大学电气工程与自动化学院,福建福州350116 [2]漳州供电公司,福建漳州363000

出　　处：《南昌大学学报（工科版）》2015年第4期396-399,404,共5页Journal of Nanchang University(Engineering & Technology)

摘　　要：在传统灰色Verhulst模型的基础上,提出无偏灰色Verhulst-markov模型,通过无偏灰色Verhulst模型,更好地解决了数据量偏少和受特定负荷数据类型的影响,同时,通过马尔科夫链进行状态估计,提高预测的误差精度。算例结果表明:无偏灰色Verhulst-markov模型在中长期负荷预测中具有较高的预测精度。On the basis of traditional grey Verhulst model,unbiased grey Verhulst-markov model was put forward. The unbiased grey Verhulst model better solved the problem of less data quantity and influence of specific load data types. At the same time,the error of the prediction accuracy was further improved through the markov chain state estimation. The results showed that the unbiased grey Verhulst-markov model has higher prediction accuracy in the middle and long term load forecasting.

关 键 词：灰色理论 灰色VERHULST模型 无偏灰色Verhulst模型 马尔科夫链 中长期负荷预测 

分 类 号：TM715[电气工程—电力系统及自动化]