The acceleration approach to practical stability domain estimation in power systems

Ribbens-Pavella, M.; Murthy, Pramod; Horward, J.L.

doi:10.1109/cdc.1981.269568

Cited by 16 publications

(5 citation statements)

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“…As for condition (ii), among the large variety of solutions proposed are the methods of [Athay et aI., 1979], of [Kakimoto et aI., 1980], the acceleration approach [Ribbens-Pavella et aI., 1981], the BCU or exit point [Chiang et aI., 1991], the PEBS [Pai, 1989], and the IPEBS methods [Fonseca and Decker, 1985].…”

Section: Anticipated Advantages and Difficulties Metmentioning

confidence: 99%

Transient Stability of Power Systems

Pavella¹,

Ernst²,

Ruiz-Vega³

2000

390

114

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Section: Anticipated Advantages and Difficulties Metmentioning

confidence: 99%

Transient Stability of Power Systems

Pavella¹,

Ernst²,

Ruiz-Vega³

2000

390

114

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“…There are many different methods of generating the V(x) Lyapunov function for the stability problem of multimachine power systems [1][2][3][4][5][6][7][8][9][10][11][12][13][14][16][17][18]. The discovery of an optimum V(x) function that gives a stability region closed to the actual one for each power system is not an easy task.…”

Section: Introductionmentioning

confidence: 99%

Analysis of transient stability of a multimachine power system using a variable gradient Lyapunov function

Machias

1986

IEE Proc. C Gener. Transm. Distrib. UK

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A new Lyapunov function for multimachine power systems with and without speed governors is generated using the variable gradient method. The method is based upon the assumption of a variable gradient function from which both V(x) and V(x) may be determined. The n unknown elements of each of the n components of the variable gradient are determined from constraints on V(x) and the generalised curl equations. The procedure given is suitable for any type of speed governor with any number of state variables. A 4-machine power system is tested and studied using both the classical step-by-step method and the Lyapunov second method. A comparative analysis between those methods indicates a great time saving for the second method. The effect of machine parameters on the critical clearing time is also investigated. Gi(s)V{x) V(x) VV(x) [yv( X )y 'max 1 = rotor angle of the ith machine = postfault stable equilibrium rotor angle of the ith machine x ( = <5, -d is c i+n = rotor speed of the ith machine = moment of inertia of the ith machine = damping coefficient of the ith machine = transfer conductance (susceptance) between the ith and the;th machines = internal voltage of the ith machine = critical clearing time = initial mechanical input power at the ith machine = mechanical power input at the ith machine = loop gain of the governing system of the ith machine = equivalent time constant of the governor of the ith machine = time constant of the prime mover of the ith machine = 2nf, P = d/dt •=• m-dimensional vector representing the states of the governor of the ith machine = m x m matrix = m-dimensional vector = m-dimensional vector = transfer function of the governor of the ith machine = Lyapunov function = time derivative of V(x) = gradient of the scalar function V(x) = transpose of V V(x) vector = ith element of V V{x) vector = (V(x)) crit

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“…As CGG is a set of generators tending to separate from the system, generators with advanced angles at the fault clearing instance are considered to be critical generator candidates [10]. Generators with small advanced angles at the moment of fault clearing can have small synchronizing power.…”

Section: Determination Of Cggmentioning

confidence: 99%

Determination of Critical Generator Group Using Accelerating Power and Synchronizing Power Coefficient in the Transient Energy Function Method

Chun¹

2011

Journal of Electrical Engineering and Technology

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-This paper proposes an algorithm for determining critical generator lists using accelerating power and synchronizing power coefficient (SPC), and critical generator group (CGG) from CGG candidates, which is a combination of critical generators. The accurate determination of CGG provides a more accurate energy margin while providing system operator with information of possible unstable generator group. Classical transient energy function (TEF) method selects the critical generators with big corrected kinetic energy of each generator at the moment of fault removal. However, the generator with small acceleration after fault, that is, the generator with small corrected kinetic energy, is also likely to belong to CGG if the generator has small synchronizing power. The proposed algorithm has been verified to be effective compared with the classical TEF method. We utilized the power system of Korean Electric Power Corporation(KEPCO) as a test system.

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The acceleration approach to practical stability domain estimation in power systems

Cited by 16 publications

References 1 publication

Transient Stability of Power Systems

Transient Stability of Power Systems

Analysis of transient stability of a multimachine power system using a variable gradient Lyapunov function

Determination of Critical Generator Group Using Accelerating Power and Synchronizing Power Coefficient in the Transient Energy Function Method

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