An Approach to the Initialization of Dynamic Induction Motor Models

Ruiz-Vega,; Asiain,; Olguin,

doi:10.1109/mper.2002.4312297

Cited by 5 publications

(8 citation statements)

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“…Therefore, initialisation of dynamic states using this method are not precise. There are several methods in literature [4,[6][7][8][9][10][11][12][13][14][15] to overcome this initialisation problem.…”

Section: Introductionmentioning

confidence: 99%

“…This method may not give reliable results as it involves approximations in reactive power calculations. Alternate PQ methods are proposed in [7,8] where, for the fixed active power, quadratic equation formed in terms of slip is solved for every iteration with the obtained values of voltage in Newton-Raphson (NR) load flow. Reactive power corresponding to this slip and voltage is updated for next iteration.…”

Section: Introductionmentioning

confidence: 99%

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New unified NR power flow algorithm for initialising fixed speed wind generation system with turbine characteristics

Varma¹,

Kumar²

2019

IET Renewable Power Generation

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Fixed speed induction machine-based wind generators are widely used. Proper initialisation of the models representing fixed speed induction machine-based wind generators connected to grid is of primary concern for stability analysis. The initialisation of fixed speed induction generators (FSIG) has been performed using conventional power flow techniques, but there exists a reactive power mismatch which makes initialisation imprecise. Moreover, turbine characteristics along with control mechanisms are not properly included for initialising the dynamics for stability analysis. A unified Newton-Raphson (NR) method was proposed in literature to include turbine characteristics and control methods for accurate initialisation of FSIG. However, this method creates an extra node for every induction machine causing an increase in the size of the Jacobian and time of execution of power flow algorithm. A new unified-NR method, which does not need an extra node, for initialisation of grid-connected FSIG is proposed in the present work. The proposed unified NR method has been validated on 14-bus, 41-bus, 203-bus, and 1336-bus test systems. The results of the proposed new unified-NR method are compared with existing unified-NR method. The results clearly demonstrate that the proposed method initialisation is accurate with considerably less computational time as compared to existing unified-NR.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New unified NR power flow algorithm for initialising fixed speed wind generation system with turbine characteristics

Varma¹,

Kumar²

2019

IET Renewable Power Generation

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“…In the literatures, there are 2 main approaches that are used to solve the problem of reactive‐power mismatch. A sequential iterative approach is a technique to solve power‐flow and motor variables separately . At every iteration, the power network is solved.…”

Section: Introductionmentioning

confidence: 99%

“…Difference between actual and bus initial reactive power is resolved by adding shunt reactive‐power compensator . Making use of the shunt compensator can affect the outcome of dynamic simulation . This approach is commonly found in some commercial power‐system simulation software tools…”

Section: Introductionmentioning

confidence: 99%

Accurate power-flow initialization of double-cage induction motors using unified Newton-Raphson method

Aree

2017

Int Trans Electr Energ Syst

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Summary An initialization of power system dynamic simulation using conventional power‐flow model is not suitable for induction motor load due to unavoidable mismatch between prespecified reactive powers from power‐flow calculation and the ones actually required by motor dynamic model. To eliminate the undesired mismatch, this paper presents a unified method for simultaneously solving power‐network and motor variables in single frame of reference using Newton‐Raphson algorithm for getting a good rate of convergence. An advanced inverse‐Γ model of double‐cage induction motors is newly developed to perform the initialization with minimum extra power‐flow variables. An ability of the unified Newton‐Raphson algorithm is demonstrated using IEEE‐300bus and 118bus systems with large numbers of groups of induction motors. The studied results show that the unified algorithm yields a correct steady‐state initialization without presence of reactive‐power mismatch and also retains a good quadratic convergence characteristic.

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“…The set of equations (28) through (37) are useful for estimating the reactive power output from induction generators [6].…”

Section: Reactive Power Initialization Without Full Scale Dynamic mentioning

confidence: 99%

Power flow and stability models for induction generators used in wind turbines

Nandigam

Chowdhury

IEEE Power Engineering Society General Meeting, 2004.

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Model initialization of the induction generator for wind power generation is investigated.Incorrect initialization may lead to numerical instability problems, not to mention erroneous results from dynamic simulations. The machine model is studied from the perspective of slip and reactive power calculation and tested for various cases. The dynamic reactive power calculation in well-known software package is discussed and the deviation of dynamic reactive power from the steady state reactive power is highlighted.Index terms --Dynamic induction machine model, load flow studies with induction generator, dynamic stability, model initialization.

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An Approach to the Initialization of Dynamic Induction Motor Models

Cited by 5 publications

References 0 publications

New unified NR power flow algorithm for initialising fixed speed wind generation system with turbine characteristics

New unified NR power flow algorithm for initialising fixed speed wind generation system with turbine characteristics

Accurate power-flow initialization of double-cage induction motors using unified Newton-Raphson method

Power flow and stability models for induction generators used in wind turbines

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