The design of turbine-generator optimal controllers including the effect of torsional modes of oscillation

Asgharian, R.; Macdonald, D. C.

doi:10.1109/60.4723

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1993

2015

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Cited by 8 publications

(2 citation statements)

References 9 publications

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“…The parameters of the generator, AVR and exciter, turbine and governor, and network are given as follows [26,27]:…”

Section: Appendixmentioning

confidence: 99%

A New Fast and Efficient Artificial Neural Network Based State Estimator Incorporated into a Linear Optimal Regulator for Power System Control Enhancement

Jazaeri

Nasrabadi

2015

Electric Power Components and Systems

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“…The parameters of the generator, AVR and exciter, turbine and governor, and network are given as follows [26,27]:…”

Section: Appendixmentioning

confidence: 99%

A New Fast and Efficient Artificial Neural Network Based State Estimator Incorporated into a Linear Optimal Regulator for Power System Control Enhancement

Jazaeri

Nasrabadi

2015

Electric Power Components and Systems

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“…Asgharian and D.C. Macdonald [3] suggested an optimal linear control system for designing auxiliary signal controllers for turbine generators. The design take into the concern the torsional mode oscillation of the rotor to obtain the best performance.…”

Section: Introductionmentioning

confidence: 99%

Optimal Controller Design for a Turbogenerator Automatic Voltage Regulator and Governor using Two Degree of Freedom Linear Quadratic Gaussian (2DOFLQG)

Tuaimah¹,

Al-rawi²,

Mahmoud³

2014

IJCA

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This paper introduces a computational methodology that adopted a method of Linear Quadratic Gaussian (LQG) controller as Automatic Voltage Regulator (AVR) and Governor to control the generator terminal voltage and the turbine speed. In this method the models were assumed to be Linear, depending on this method the controller power consumption was minimized depending on some performance index, which is assumed to be Quadratic. This method was taken into account the noise and the disturbance in view, considered its distribution as Gaussian. The two degree of freedom (2DOF) structure was adopted, in which two controllers are used. The effectiveness of the proposed control action is demonstrated through some computer simulations on a Single-Machine Infinite-Bus (SMIB) power system.To accommodate stability requirements, a mathematical model for the generator and the turbine was derived based on the twoaxis theorem and starting from the swing equation. Results obtained show that adopting such a controller enhanced the steady state and transient stability.

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Turbine generator laboratory model tests to damp torsional oscillations with supplementary signals

Sokhey¹,

Limebeer

Macdonald

1993

IEEE Trans. On energy Conversion

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The design of turbine-generator optimal controllers including the effect of torsional modes of oscillation

Cited by 8 publications

References 9 publications

A New Fast and Efficient Artificial Neural Network Based State Estimator Incorporated into a Linear Optimal Regulator for Power System Control Enhancement

A New Fast and Efficient Artificial Neural Network Based State Estimator Incorporated into a Linear Optimal Regulator for Power System Control Enhancement

Optimal Controller Design for a Turbogenerator Automatic Voltage Regulator and Governor using Two Degree of Freedom Linear Quadratic Gaussian (2DOFLQG)

Turbine generator laboratory model tests to damp torsional oscillations with supplementary signals

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