Short-term load forecasting based on support vector machine combined with clustering

被引：0
|
作者：
Gao, Rong [1 ]
Liu, Xiaohua [1 ]
机构：
[1] LuDong Univ, Sch Math & Informat, Yantai 264025, Peoples R China
来源：
General System and Control System, Vol I | 2007年
关键词：
load forecasting; support vector machine; clustering;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Load forecasting has always been the essential part of an efficient power system planning and operation. The model combined support vector machine (svm) and clustering algorithm. Clustering algorithm is used to group data with similar characteristics and svm plays a role of function approximation to capture the underlying characteristics of each cluster of data A demonstration of the proposed methodology is performed for the one-step ahead forecasting of load data from the Shan Dong power system. The analysis of the forecasting result showed that the proposed method is effective.
引用
收藏
页码：135 / 138
页数：4
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