The application of neural network controller to power system with SMES for transient stability enhancement

A. Demirören; H. L. Zeynelgil; S. N. Sengör

doi:10.1002/etep.109

The application of neural network controller to power system with SMES for transient stability enhancement

A. Demirören^*, H. L. Zeynelgil, S. N. Sengör

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

In this paper, a synchronous generator including power system stabilizer (PSS), voltage regulator, and governor is considered. This generator also has a superconducting magnetic energy storage (SMES) unit at its terminal bus. The investigation of the transient stability enhancement for the whole system is done using SMES unit and neural network (NN) controllers, while one of the controllers affects the mechanical input; the other affects the exciter input. Thus, non-linear power system control is provided by a control application of layered neural networks. The back propagation-through-time algorithm is used as a control rule for the NN controller.

Original language	English
Pages (from-to)	629-646
Number of pages	18
Journal	European Transactions on Electrical Power
Volume	16
Issue number	6
DOIs	https://doi.org/10.1002/etep.109
Publication status	Published - Nov 2006

Keywords

NN
Power system
PSS
SMES

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10.1002/etep.109

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title = "The application of neural network controller to power system with SMES for transient stability enhancement",

abstract = "In this paper, a synchronous generator including power system stabilizer (PSS), voltage regulator, and governor is considered. This generator also has a superconducting magnetic energy storage (SMES) unit at its terminal bus. The investigation of the transient stability enhancement for the whole system is done using SMES unit and neural network (NN) controllers, while one of the controllers affects the mechanical input; the other affects the exciter input. Thus, non-linear power system control is provided by a control application of layered neural networks. The back propagation-through-time algorithm is used as a control rule for the NN controller.",

keywords = "NN, Power system, PSS, SMES",

author = "A. Demir{\"o}ren and Zeynelgil, {H. L.} and Seng{\"o}r, {S. N.}",

year = "2006",

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AU - Demirören, A.

AU - Zeynelgil, H. L.

AU - Sengör, S. N.

PY - 2006/11

Y1 - 2006/11

N2 - In this paper, a synchronous generator including power system stabilizer (PSS), voltage regulator, and governor is considered. This generator also has a superconducting magnetic energy storage (SMES) unit at its terminal bus. The investigation of the transient stability enhancement for the whole system is done using SMES unit and neural network (NN) controllers, while one of the controllers affects the mechanical input; the other affects the exciter input. Thus, non-linear power system control is provided by a control application of layered neural networks. The back propagation-through-time algorithm is used as a control rule for the NN controller.

AB - In this paper, a synchronous generator including power system stabilizer (PSS), voltage regulator, and governor is considered. This generator also has a superconducting magnetic energy storage (SMES) unit at its terminal bus. The investigation of the transient stability enhancement for the whole system is done using SMES unit and neural network (NN) controllers, while one of the controllers affects the mechanical input; the other affects the exciter input. Thus, non-linear power system control is provided by a control application of layered neural networks. The back propagation-through-time algorithm is used as a control rule for the NN controller.

KW - NN

KW - Power system

KW - PSS

KW - SMES

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EP - 646

JO - European Transactions on Electrical Power

JF - European Transactions on Electrical Power

IS - 6

ER -

The application of neural network controller to power system with SMES for transient stability enhancement

Abstract

Keywords

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