DocumentCode
2671926
Title
An Introduction to the Echo State Network and its Applications in Power System
Author
Dai, Jing ; Venayagamoorthy, Ganesh K. ; Harley, Ronald G.
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear
2009
fDate
8-12 Nov. 2009
Firstpage
1
Lastpage
7
Abstract
Echo state network (ESN) is a new type of recurrent neural network (RNN) proposed in recent years. The training process of ESN is easier and requires less computational effort than regular RNN which has the same size. Due to its high modeling capability of complex dynamic system, ESN has been used in various power system applications such as power system nonlinear load modeling and true harmonic current detection, wide area monitoring, intelligent control of an active power filter (APF), overhead conductor thermal dynamics identification, wind speed or water inflow forecasting, etc. This paper introduces the basic concept and the offline and online training algorithms of the ESN in detail and reviews the state of the art of ESN applications in power systems.
Keywords
learning (artificial intelligence); power system harmonics; power system measurement; power system simulation; recurrent neural nets; active power filter; echo state network; overhead conductor thermal dynamics identification; power system nonlinear load modeling; recurrent neural network; true harmonic current detection; wide area monitoring; Active filters; Nonlinear dynamical systems; Power harmonic filters; Power system control; Power system dynamics; Power system harmonics; Power system modeling; Power systems; Predictive models; Recurrent neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent System Applications to Power Systems, 2009. ISAP '09. 15th International Conference on
Conference_Location
Curitiba
Print_ISBN
978-1-4244-5097-8
Type
conf
DOI
10.1109/ISAP.2009.5352913
Filename
5352913
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