A Novel Approach for Short-Term Electric Load Forecasting

被引：0

作者：

Wu, Xiaoqin ^{[1
,2
]}

Shen, Zhixi ^{[1
,2
]}

Song, Yongduan ^{[1
,2
]}

机构：

[1] Chongqing Univ, Key Lab Dependable Serv Comp Cyber, Phys Soc, Minist Educ, Chongqing 400044, Peoples R China

[2] Chongqing Univ, Sch Automat, Chongqing 400044, Peoples R China

来源：

PROCEEDINGS OF THE 2016 12TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2016年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Rapid and accurate load forecasting is vital for renewable yet highly stochastic power (such as wind and solar power) to be massively utilized in practice. The model-based forecasting algorithms are derived from the specific load models. This paper proposes a new approach for load forecasting in power systems by using trajectory tracking stability theory. And based upon Lyapunov stability theory, the the proposed method is essentially model independent and can ensure the prediction error convergence.

引用

页码：1999 / 2002

页数：4

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