A similar day selection method for load forecasting based on unsupervised support vector machine

被引：0

作者：

Liu, Chaonan ^{[1
]}

Pan, Zhiyuan ^{[1
]}

Jing, Hui ^{[1
]}

机构：

[1] State Grid China Technol Coll, Jinan, Peoples R China

来源：

ADVANCES IN ENERGY SCIENCE AND EQUIPMENT ENGINEERING | 2015年

关键词：

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Load forecasting is the basis for the security and economy of power system operation, and a reasonable method of similar day selection will help to improve the accuracy of load forecasting. But it cannot always reach the best effect according to the similar days selected by artificial experience. In order to improve the accuracy of load forecasting, the paper proposed a new unsupervised support vector machine model to select the similar days, based on the analysis of the influences on the load variation characteristic. And an example is given to prove the validity of the method.

引用

页码：1423 / 1427

页数：5

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