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. © 2009 IEEE.
Recommended Citation
J. Dai et al., "An Introduction to the Echo State Network and its Applications in Power System," 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09, article no. 5352913, Institute of Electrical and Electronics Engineers, Dec 2009.
The definitive version is available at https://doi.org/10.1109/ISAP.2009.5352913
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-142445098-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
09 Dec 2009
